26.1.4 Financial Analysis, Business Systems

Tinù, P.[Peter], Schittenkopf, C.[Christian], Dorffner, G.[Georg],
Volatility Trading via Temporal Pattern Recognition in Quantised Financial Time Series,
PAA(4), No. 4 2001, pp. 283-299.
Springer DOI 0202
BibRef

Keilis-Borok, V.I., Soloviev, A.A., Allègre, C.B., Sobolevskii, A.N., Intriligator, M.D.,
Patterns of macroeconomic indicators preceding the unemployment rise in Western Europe and the USA,
PR(38), No. 3, March 2005, pp. 423-435.
Elsevier DOI 0412
BibRef

Anderson, B.B., Hansen, J.V., Lowry, P.B., Summers, S.L.,
Model checking for E-business control and assurance,
SMC-C(35), No. 3, August 2005, pp. 445-450.
IEEE DOI 0508
BibRef

Nanni, L.[Loris],
Multi-resolution subspace for financial trading,
PRL(27), No. 2, 15 January 2006, pp. 109-115.
Elsevier DOI 0512
BibRef

Yümlü, S.[Serdar], Gürgen, F.S.[Fikret S.], Okay, N.[Nesrin],
A comparison of global, recurrent and smoothed-piecewise neural models for Istanbul stock exchange (ISE) prediction,
PRL(26), No. 13, 1 October 2005, pp. 2093-2103.
Elsevier DOI 0509
BibRef

Mishra, S.K.[Sudhansu Kumar], Panda, G.[Ganapati], Meher, S.[Sukadev], Majhi, R.[Ritanjali],
Multi-objective evolutionary algorithms for financial portfolio design,
IJCVR(1), No. 2, 2010, pp. 236-247.
DOI Link 1011
BibRef

Frasca, M.[Marco], Farina, A.[Alfonso],
Tartaglia-Pascal triangle and Brownian motion in non-euclidean geometries: application to heat and Black-Scholes equations,
SIViP(8), No. 6, September 2014, pp. 1149-1157.
Springer DOI 1408
Financial models. BibRef

Yang, Y.[Yi], Liu, J.P.[Ji-Ping], Xu, S.H.[Sheng-Hua], Zhao, Y.Y.[Yang-Yang],
An Extended Semi-Supervised Regression Approach with Co-Training and Geographical Weighted Regression: A Case Study of Housing Prices in Beijing,
IJGI(5), No. 1, 2016, pp. 4.
DOI Link 1602
BibRef

Donnat, P.[Philippe], Marti, G.[Gautier], Very, P.[Philippe],
Toward a generic representation of random variables for machine learning,
PRL(70), No. 1, 2016, pp. 24-31.
Elsevier DOI 1602
Financial time series BibRef

Cao, N., Brahma, S., Varshney, P.K.,
Optimal Auction Design With Quantized Bids,
SPLetters(23), No. 11, November 2016, pp. 1518-1522.
IEEE DOI 1609
commerce BibRef

Lee, E.J.[Eun-Jin], Kwon, J.M.[Jung-Min],
Effects of money simulation application on persons with intellectual disabilities with money transaction difficulties,
IJCVR(6), No. 3, 2016, pp. 253-260.
DOI Link 1608
BibRef

Zhao, F.[Feng], Zhang, Y.Y.[Yu-Yi], Chen, H.B.[Hong-Bin],
Withdrawn: Multimodal data analysis and integration for multi-slot spectrum auction based on Deep Feedforward Network,
PR(72), No. 1, 2017, pp. 466-472.
Elsevier DOI 1708
BibRef
And: Withdrawn - premature publication. PR(76), No. 1, 2018, pp. 765.
Elsevier DOI 1801
Multimodal data analysis and integration BibRef

Hendricks, D.[Dieter],
Using real-time cluster configurations of streaming asynchronous features as online state descriptors in financial markets,
PRL(97), No. 1, 2017, pp. 21-28.
Elsevier DOI 1709
Online, learning BibRef

Bicego, M., Farinelli, A., Grosso, E., Paolini, D., Ramchurn, S.D.,
On the distinctiveness of the electricity load profile,
PR(74), No. 1, 2018, pp. 317-325.
Elsevier DOI 1711
Energy, market BibRef

Xiao, Y.X.[Yi-Xiong], Chen, X.[Xiang], Li, Q.A.[Qi-Ang], Yu, X.[Xi], Chen, J.[Jin], Guo, J.[Jing],
Exploring Determinants of Housing Prices in Beijing: An Enhanced Hedonic Regression with Open Access POI Data,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Lewandowska-Gwarda, K.[Karolina],
Geographically Weighted Regression in the Analysis of Unemployment in Poland,
IJGI(7), No. 1, 2018, pp. xx-yy.
DOI Link 1801
BibRef

Yang, P.Y.[Pei-Yi], Lai, Z.R.[Zhao-Rong], Wu, X.T.[Xiao-Tian], Fang, L.D.[Liang-Da],
Trend representation based log-density regularization system for portfolio optimization,
PR(76), No. 1, 2018, pp. 14-24.
Elsevier DOI 1801
Trend representation BibRef

Gómez, J.A.[Jon Ander], Arévalo, J.[Juan], Paredes, R.[Roberto], Nin, J.[Jordi],
End-to-end neural network architecture for fraud scoring in card payments,
PRL(105), 2018, pp. 175-181.
Elsevier DOI 1804
Fraud detection, Credit card payments, Deep learning, Neural networks BibRef

Ceh, M.[Marjan], Kilibarda, M.[Milan], Lisec, A.[Anka], Bajat, B.[Branislav],
Estimating the Performance of Random Forest versus Multiple Regression for Predicting Prices of the Apartments,
IJGI(7), No. 5, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Paulin, J., Calinescu, A., Wooldridge, M.,
Agent-Based Modeling for Complex Financial Systems,
IEEE_Int_Sys(33), No. 2, March 2018, pp. 74-82.
IEEE DOI 1806
Adaptation models, Biological system modeling, Computer crashes, Economics, Financial management, Investment, financial, simulation modeling and visualization BibRef

Tiamaz, Y., Souissi, N.,
Classification of the lean implementation procedures for improving the business processes,
ISCV18(1-6)
IEEE DOI 1807
business data processing, business process re-engineering, lean production, pattern classification, Classification, Tools BibRef

Ma, K., Wang, C., Yang, J., Hua, C., Guan, X.,
Pricing Mechanism With Noncooperative Game and Revenue Sharing Contract in Electricity Market,
Cyber(49), No. 1, January 2019, pp. 97-106.
IEEE DOI 1901
Games, Supply chains, Companies, Contracts, Load management, Load forecasting, Electricity supply industry, revenue sharing contract (RSC) BibRef

Brackin, R.C.[Roger C.], Jackson, M.J.[Michael J.], Leyshon, A.[Andrew], Morley, J.G.[Jeremy G.],
Taming Disruption? Pervasive Data Analytics, Uncertainty and Policy Intervention in Disruptive Technology and its Geographic Spread,
IJGI(8), No. 1, 2019, pp. xx-yy.
DOI Link 1901
BibRef

Hu, X.B.[Xian-Biao], Zhu, X.Y.[Xiao-Yu], Ma, Y.L.[Yu-Luen], Chiu, Y.C.[Yi-Chang], Tang, Q.[Qing],
Advancing usage-based insurance: A contextual driving risk modelling and analysis approach,
IET-ITS(13), No. 3, March 2019, pp. 453-460.
DOI Link 1903
BibRef

Cai, Z.Q.[Zhao-Quan], Chen, G.C.[Guang-Cai], Xing, L.N.[Li-Ning], Yang, J.H.[Jing-Hui], Tan, X.[Xu],
Evaluating hedge fund downside risk using a multi-objective neural network,
JVCIR(59), 2019, pp. 433-438.
Elsevier DOI 1903
Downside risk evaluation, Big data hedge fund, Multi-objective neural network BibRef

Ma, D.F.[Dong-Fang], Li, W.J.[Wen-Jing], Song, X.[Xiang], Wang, Y.H.[Yin-Hai], Zhang, W.B.[Wei-Bin],
Time-of-day breakpoints optimisation through recursive time series partitioning,
IET-ITS(13), No. 4, April 2019, pp. 683-692.
DOI Link 1903
BibRef

Liu, C.Y.[Cheng-Yong], Chiou, L.J.[Ling-Jan], Li, C.C.[Cheng-Chung], Ye, X.W.[Xiu-Wen],
Analysis of Beijing Tianjin Hebei regional credit system from the perspective of big data credit reporting,
JVCIR(59), 2019, pp. 300-308.
Elsevier DOI 1903
SVM, Information asymmetry, Convolution neural network, Decision tree, Credit investigation BibRef

Adamiak, C.[Czeslaw], Szyda, B.[Barbara], Dubownik, A.[Anna], García-Álvarez, D.[David],
Airbnb Offer in Spain: Spatial Analysis of the Pattern and Determinants of Its Distribution,
IJGI(8), No. 3, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Tripathi, V.[Vikas], Mittal, A.[Ankush], Gangodkar, D.[Durgaprasad], Kanth, V.[Vishnu],
Real time security framework for detecting abnormal events at ATM installations,
RealTimeIP(16), No. 2, April 2019, pp. 535-545.
Springer DOI 1904
BibRef

Herrera Silva, J.A.[Juan A.], Barona López, L.I.[Lorena Isabel], Valdivieso Caraguay, Á.L.[Ángel Leonardo], Hernández-Álvarez, M.[Myriam],
A Survey on Situational Awareness of Ransomware Attacks: Detection and Prevention Parameters,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Shen, W.[Wei], Qin, Y.C.[Yao-Chen], Xie, Z.X.[Zhi-Xiang],
Research on the Spatial Features of the E-Retailing-Economic Linkages at County Level: A Case Study for Zhejiang Province, China,
IJGI(8), No. 8, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Garcia, C.[Cristiano], Esmin, A.[Ahmed], Leite, D.[Daniel], Škrjanc, I.[Igor],
Evolvable fuzzy systems from data streams with missing values: With application to temporal pattern recognition and cryptocurrency prediction,
PRL(128), 2019, pp. 278-282.
Elsevier DOI 1912
Temporal pattern recognition, On-line algorithm, Real-time system, Fuzzy system, Machine learning BibRef

Moghadasian, S.S., Gazor, S.,
Sparsely Localized Time-Frequency Energy Distributions for Multi-Component LFM Signals,
SPLetters(27), 2020, pp. 6-10.
IEEE DOI 2001
Time-frequency analysis, Signal resolution, Fourier transforms, Simulation, Ambiguity, localization, sparsity, chirp BibRef

Deshmukh, S., Dubey, A.,
Improved Covariance Matrix Estimation With an Application in Portfolio Optimization,
SPLetters(27), 2020, pp. 985-989.
IEEE DOI 2007
Covariance matrices, Portfolios, Eigenvalues and eigenfunctions, Optimization, Correlation, Estimation, Noise measurement, Random Matrix Theory BibRef

Passalis, N.[Nikolaos], Tefas, A.[Anastasios], Kanniainen, J.H.[Ju-Ho], Gabbouj, M.[Moncef], Iosifidis, A.[Alexandros],
Temporal logistic neural Bag-of-Features for financial time series forecasting leveraging limit order book data,
PRL(136), 2020, pp. 183-189.
Elsevier DOI 2008
Limit order book data, Bag-of-Features, Time-series forecasting BibRef

Ma, C.[Chao], Liu, Z.B.[Zhen-Bing], Cao, Z.G.[Zhi-Guang], Song, W.[Wen], Zhang, J.[Jie], Zeng, W.L.[Wei-Liang],
Cost-sensitive deep forest for price prediction,
PR(107), 2020, pp. 107499.
Elsevier DOI 2008
Cost-sensitive Deep Forest, Ensemble Deep Learning, Price Prediction, Modified K-means BibRef

Guo, Y.P.[Yi-Ping],
Credit risk assessment of P2P lending platform towards big data based on BP neural network,
JVCIR(71), 2020, pp. 102730.
Elsevier DOI 2009
Peer to peer, Credit risk assessment, Logistic regression, BP neural network, Big data BibRef

Wang, Y.P.[Yu-Peng],
Analysis of financial business model towards big data and its applications,
JVCIR(71), 2020, pp. 102729.
Elsevier DOI 2009
Financial business, Big data, Neural network BibRef

Li, M.[Meng], Zhang, K.[Keli], Liu, J.[Jiamou], Gong, H.X.[Han-Xiao], Zhang, Z.J.[Zi-Jian],
Blockchain-based anomaly detection of electricity consumption in smart grids,
PRL(138), 2020, pp. 476-482.
Elsevier DOI 1806
Smart grids, Electricity consumption, Anomaly detection, Blockchain BibRef

Liu, W.D.[Wei-Dong], Liu, X.[Xin], Qiao, W.B.[Wen-Bo],
Probabilistic graph-based valuation model for measuring the relative patent value in a valuation scenario,
PRL(138), 2020, pp. 204-210.
Elsevier DOI 2010
Patent value, Probabilistic graphical model BibRef

Zhao, J.J.[Jie-Jie], Du, B.[Bowen], Sun, L.L.[Lei-Lei], Lv, W.F.[Wei-Feng], Liu, Y.[Yanchi], Xiong, H.[Hui],
Deep multi-task learning with relational attention for business success prediction,
PR(110), 2021, pp. 107469.
Elsevier DOI 2011
Multi-task learning, Attention, Site selection BibRef

Amato, A.[Alberto], Quarto, A.[Alessandro], di Lecce, V.[Vincenzo],
An application of cyber-physical system and multi-agent technology to demand-side management systems,
PRL(141), 2021, pp. 23-31.
Elsevier DOI 2101
Cyber-physical system, Multi-agent system, Demand-side management systems, Industry 4.0 BibRef

Sladic, G.[Goran], Milosavljevic, B.[Branko], Nikolic, S.[Siniša], Sladic, D.[Dubravka], Radulovic, A.[Aleksandra],
A Blockchain Solution for Securing Real Property Transactions: A Case Study for Serbia,
IJGI(10), No. 1, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Chen, D.D.[Dong-Dong], Guo, X.C.[Xing-Chen], Wang, J.J.[Jian-Jia], Liu, J.T.[Jia-Tong], Zhang, Z.H.[Zhi-Hong], Hancock, E.R.[Edwin R.],
Thermodynamic motif analysis for directed stock market networks,
PR(114), 2021, pp. 107872.
Elsevier DOI 2103
Cluster expansion, Motif, Directed network entropy BibRef

Li, Z.X.[Zong-Xi], Xie, H.R.[Hao-Ran], Xu, G.D.[Guan-Dong], Li, Q.[Qing], Leng, M.M.[Ming-Ming], Zhou, C.[Chi],
Towards purchase prediction: A transaction-based setting and a graph-based method leveraging price information,
PR(113), 2021, pp. 107824.
Elsevier DOI 2103
Purchase prediction, Graph-based method, e-commerce, Transaction-level data BibRef

Cui, L.X.[Li-Xin], Bai, L.[Lu], Wang, Y.[Yanchao], Jin, X.[Xin], Hancock, E.R.[Edwin R.],
Internet financing credit risk evaluation using multiple structural interacting elastic net feature selection,
PR(114), 2021, pp. 107835.
Elsevier DOI 2103
Credit risk, Feature selection, Elastic net, Sparse learning, Structural interaction, Internet financing BibRef

Li, G.[Gen], Jung, J.J.[Jason J.],
Dynamic relationship identification for abnormality detection on financial time series,
PRL(145), 2021, pp. 194-199.
Elsevier DOI 2104
Spurious relationship pattern, Dynamic relationship matrix, Abnormality detection BibRef

Chandar, S.K.[S. Kumar],
Hybrid models for intraday stock price forecasting based on artificial neural networks and metaheuristic algorithms,
PRL(147), 2021, pp. 124-133.
Elsevier DOI 2106
Artificial bee colony algorithm, Artificial neural network, Genetic algorithm, Hit rate, Intraday stock prediction, Stock market prediction BibRef

Chen, D.C.[Dao-Chang], Hu, W.Z.[Wen-Zheng], Yuan, B.[Bo], Zhang, R.[Rui], Wang, J.Q.[Jian-Qiang],
Next-Item Recommendation With Deep Adaptable Co-Embedding Neural Networks,
SPLetters(28), 2021, pp. 1220-1224.
IEEE DOI 2106
e-commerce. Training, Neural networks, Markov processes, Covariance matrices, dynamic integration BibRef

Zhou, Z.F.[Zhi-Feng], Chen, R.[Rong], Guo, S.K.[Shi-Kai],
A domain-of-influence based pricing strategy for task assignment in crowdsourcing package delivery,
IET-ITS(15), No. 6, 2021, pp. 808-823.
DOI Link 2106
BibRef

Huang, B.Y.[Bing-Yuan], Thomas, T.[Tom], Groenewolt, B.[Benjamin], Claasen, Y.[Yorick], van Berkum, E.[Eric],
Effectiveness of incentives offered by mobile phone app to encourage cycling: A long-term study,
IET-ITS(15), No. 3, 2021, pp. 406-422.
DOI Link 2106
BibRef

Xu, L.X.[Li-Xiang], Cui, L.X.[Li-Xin], Weise, T.[Thomas], Li, X.L.[Xin-Lu], Wu, Z.Z.[Zhi-Ze], Nie, F.P.[Fei-Ping], Chen, E.H.[En-Hong], Tang, Y.Y.[Yuan-Yan],
Semi-supervised multi-Layer convolution kernel learning in credit evaluation,
PR(120), 2021, pp. 108125.
Elsevier DOI 2109
Semi-supervised learning, SVM, Convolution kernel function, Random sampling, Multi-layer kernel BibRef

Wang, J.J.[Jian-Jia], Guo, X.C.[Xing-Chen], Li, W.M.[Wei-Min], Wu, X.[Xing], Zhang, Z.H.[Zhi-Hong], Hancock, E.R.[Edwin R.],
Statistical mechanical analysis for unweighted and weighted stock market networks,
PR(120), 2021, pp. 108123.
Elsevier DOI 2109
Stock market networks, Thermodynamic characterisations, Statistical mechanics BibRef

Cheng, D.W.[Da-Wei], Yang, F.Z.[Fang-Zhou], Xiang, S.[Sheng], Liu, J.[Jin],
Financial time series forecasting with multi-modality graph neural network,
PR(121), 2022, pp. 108218.
Elsevier DOI 2109
Graph neural network, Graph attention, Deep learning, Quantitative investment BibRef

Wu, L.[Likang], Li, Z.[Zhi], Zhao, H.[Hongke], Liu, Q.[Qi], Chen, E.[Enhong],
Estimating fund-raising performance for start-up projects from a market graph perspective,
PR(121), 2022, pp. 108204.
Elsevier DOI 2109
Crowdfunding, Market environment modeling, Graph neural network BibRef

Feng, S.[Shibo], Xu, C.[Chen], Zuo, Y.[Yu], Chen, G.[Guo], Lin, F.[Fan], XiaHou, J.B.[Jian-Bing],
Relation-aware dynamic attributed graph attention network for stocks recommendation,
PR(121), 2022, pp. 108119.
Elsevier DOI 2109
Financial market, Attributed graph attention network, Correlation coefficient, Chinese stock recommendation BibRef

Agrahari, A.[Ashutosh], Singh, P.[Pawan], Veer, A.[Ankur], Singh, A.[Anshuman], Vidyarthi, A.[Ankit], Khan, B.[Baseem],
Prognosticating the effect on Unemployment rate in the post-pandemic India via Time-Series Forecasting and Least Squares Approximation,
PRL(152), 2021, pp. 172-179.
Elsevier DOI 2112
ARIMA, Corona virus, unemployment, time-series forecasting, Prophet, Least squares approximation, vector approximation BibRef

Nalmpantis, A.[Angelos], Passalis, N.[Nikolaos], Tsantekidis, A.[Avraam], Tefas, A.[Anastasios],
Deep adaptive group-based input normalization for financial trading,
PRL(152), 2021, pp. 413-419.
Elsevier DOI 2112
BibRef

Tai, W.X.[Wen-Xin], Zhong, T.[Ting], Mo, Y.H.[Yu-Hua], Zhou, F.[Fan],
Learning Sentimental and Financial Signals With Normalizing Flows for Stock Movement Prediction,
SPLetters(29), 2022, pp. 414-418.
IEEE DOI 2202
Predictive models, Time series analysis, Stochastic processes, Data models, Noise measurement, Task analysis, generative models BibRef

Latpate, R.[Raosaheb], Kurade, S.S.[Sandesh S.],
Multi-Objective Multi-Index Transportation Model for Crude Oil Using Fuzzy NSGA-II,
ITS(23), No. 2, February 2022, pp. 1347-1356.
IEEE DOI 2202
Oils, Transportation, Optimization, Indexes, Mathematical model, Business, Genetic algorithms, Crude oil, triangular fuzzy number BibRef

Zhang, W.P.[Wei-Peng], Zhang, N.[Ning], Yan, J.C.[Jun-Chi], Li, G.[Guofu], Yang, X.K.[Xiao-Kang],
Auto uning of price prediction models for high-frequency trading via reinforcement learning,
PR(125), 2022, pp. 108543.
Elsevier DOI 2203
High-frequency trading, Inverse reinforcement learning, Parameter optimization, Multi-armed bandit BibRef

Zhang, W.P.[Wei-Peng], Wang, L.[Lu], Xie, L.[Liang], Feng, K.[Ke], Liu, X.[Xiang],
TradeBot: Bandit learning for hyper-parameters optimization of high frequency trading strategy,
PR(124), 2022, pp. 108490.
Elsevier DOI 2203
High-Frequency trading, Hyper-parameter optimization, Multi-armed bandit learning, Inverse reinforcement learning BibRef

Jing, C.F.[Chang-Feng], Guo, S.[Shasha], Zhang, H.Y.[Hong-Yang], Lv, X.X.[Xin-Xin], Wang, D.L.[Dong-Liang],
SmartEle: Smart Electricity Dashboard for Detecting Consumption Patterns: A Case Study at a University Campus,
IJGI(11), No. 3, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Parvaneh, A.[Amin], Abbasnejad, E.[Ehsan], Wu, Q.[Qi], Shi, J.Q.F.[Javen Qin-Feng], van den Hengel, A.J.[Anton J.],
Show, Price and Negotiate: A Negotiator With Online Value Look-Ahead,
MultMed(24), 2022, pp. 1426-1434.
IEEE DOI 2204
Visualization, Decoding, Australia, Task analysis, Neural networks, History, Estimation, Goal-oriented dialogue system, visual negotiation BibRef

Cheng, L.X.[Lu-Xiao], Feng, R.[Ruyi], Wang, L.Z.[Li-Zhe], Yan, J.N.[Ji-Ning], Liang, D.[Dong],
An Assessment of Electric Power Consumption Using Random Forest and Transferable Deep Model with Multi-Source Data,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Gao, W.[Wei], Yang, H.Z.[Hai-Zhong],
Time-varying Group Lasso Granger Causality Graph for High Dimensional Dynamic system,
PR(130), 2022, pp. 108789.
Elsevier DOI 2206
Time-varying Granger causality, Feature selection, Group Lasso, Financial market network BibRef

Wang, Z.D.[Zheng-Di], Yang, L.Q.[Lv-Qing], Lei, Z.F.[Zhen-Feng], Ul Haq, A.[Anwar], Zhang, D.[Defu], Yang, S.Y.[Shuang-Yuan], Francis, A.O.[Akindipe Olusegun],
An entity-weights-based convolutional neural network for large-sale complex knowledge embedding,
PR(131), 2022, pp. 108841.
Elsevier DOI 2208
Graph-based finance, Representation learning, Complete incidence matrix, Convolutional neural network, Matrix factorization BibRef

Cao, T.W.[Tian-Wei], Xu, Q.Q.[Qian-Qian], Yang, Z.Y.[Zhi-Yong], Huang, Q.M.[Qing-Ming],
Meta-Wrapper: Differentiable Wrapping Operator for User Interest Selection in CTR Prediction,
PAMI(44), No. 11, November 2022, pp. 8449-8464.
IEEE DOI 2210
Click-through-rate. Feature extraction, Predictive models, Wrapping, Frequency modulation, Computational modeling, Training, meta-learning BibRef

Fatima, G.[Ghania], Babu, P.[Prabhu], Stoica, P.[Petre],
Covariance Matrix Estimation Under Positivity Constraints With Application to Portfolio Selection,
SPLetters(29), 2022, pp. 2487-2491.
IEEE DOI 2212
Covariance matrices, Signal processing algorithms, Portfolios, Maximum likelihood estimation, Codes, Optimization, Correlation, portfolio selection BibRef

Ebrahimi, M.[Mohammadreza], Chai, Y.D.[Yi-Dong], Zhang, H.H.[Hao Helen], Chen, H.[Hsinchun],
Heterogeneous Domain Adaptation With Adversarial Neural Representation Learning: Experiments on E-Commerce and Cybersecurity,
PAMI(45), No. 2, February 2023, pp. 1862-1875.
IEEE DOI 2301
Optimization, Image recognition, Task analysis, Kernel, Adaptation models, Linear programming, Electronic commerce, transfer learning BibRef

Wang, S.[Sutong], Zhu, J.C.[Jia-Cheng], Yin, Y.Q.[Yun-Qiang], Wang, D.[Dujuan], Cheng, T.C.E.[T.C. Edwin], Wang, Y.Z.[Yan-Zhang],
Interpretable Multi-Modal Stacking-Based Ensemble Learning Method for Real Estate Appraisal,
MultMed(25), 2023, pp. 315-328.
IEEE DOI 2301
Appraisal, Learning systems, Predictive models, Costs, Regression tree analysis, Metadata, Genetic algorithms, geographical locations BibRef

Yue, X.Y.[Xiao-Yun], Xue, L.[Ling], Ji, T.H.[Tian-Hao],
A Novel Used Vehicles Price Prediction Model Based on Denoising Autoencoder With Convolution Operation,
ITS(24), No. 3, March 2023, pp. 3008-3017.
IEEE DOI 2303
Predictive models, Noise reduction, Data models, Convolution, Numerical models, Feature extraction, Computational modeling, denoising autoencoder model BibRef

Tang, Z.[Zhe], Yang, Y.[Yi], Li, W.[Wen], Lian, D.[Defu], Duan, L.X.[Li-Xin],
Deep Cross-Attention Network for Crowdfunding Success Prediction,
MultMed(25), 2023, pp. 1306-1319.
IEEE DOI 2305
Videos, Task analysis, Semantics, Fuses, Visualization, Companies, Crowdfunding success prediction, multimodal learning BibRef

Rakesh, D.K.[Deepak Kumar], Jana, P.K.[Prasanta K.],
An improved differential evolution algorithm for quantifying fraudulent transactions,
PR(141), 2023, pp. 109623.
Elsevier DOI 2306
Quantifying fraudulent transactions (QFT), Cost-based feature selection, Multiobjective optimization, Differential evolution BibRef

Shabani, M.[Mostafa], Tran, D.T.[Dat Thanh], Kanniainen, J.H.[Ju-Ho], Iosifidis, A.[Alexandros],
Augmented bilinear network for incremental multi-stock time-series classification,
PR(141), 2023, pp. 109604.
Elsevier DOI 2306
Deep learning, Low rank tensor decomposition, Limit order book data, Financial time-series analysis BibRef

Zhang, W.Y.[Wen-Yu], Li, X.M.[Xiang-Ming], Chen, Y.Z.[Yun-Zhu], Ye, N.[Neng], Zhang, X.P.[Xiao-Ping],
Effective Online Portfolio Selection for the Long-Short Market Using Mirror Gradient Descent,
SPLetters(30), 2023, pp. 913-917.
IEEE DOI 2308
Portfolios, Signal processing algorithms, Computational complexity, Instruments, Mirrors, Convex functions, future market BibRef

Cui, C.R.[Chao-Ran], Li, X.J.[Xiao-Jie], Zhang, C.Y.[Chun-Yun], Guan, W.[Weili], Wang, M.[Meng],
Temporal-Relational hypergraph tri-Attention networks for stock trend prediction,
PR(143), 2023, pp. 109759.
Elsevier DOI 2310
Stock trend prediction, Stock investment simulation, Hypergraph convolutional networks, Attention mechanism BibRef

Xi, W.Z.[Wen-Zhi], Li, Z.F.[Zhan-Feng], Song, X.Y.[Xin-Yuan], Ning, H.[Hanwen],
Online portfolio selection with predictive instantaneous risk assessment,
PR(144), 2023, pp. 109872.
Elsevier DOI 2310
Portfolio optimization, Online learning, High-dimensional covariance matrix, Ensemble learning, High-dimensional short-term data BibRef

Jiang, M.[Manrui], Chen, W.[Wei], Xu, H.L.[Hui-Lin], Liu, Y.X.[Yan-Xin],
A novel interval dual convolutional neural network method for interval-valued stock price prediction,
PR(145), 2024, pp. 109920.
Elsevier DOI 2311
Interval-valued time series, Interval-valued stock price, Stock price prediction, Relevant stock information, Convolutional neural network BibRef

Liu, W.X.[Wei-Xing], Zhang, Z.[Zunqian], Bai, Y.J.[Yun-Jie], Liu, Y.K.[Yi-Kai], Yang, A.[Aimin], Li, J.[Jie],
A DeepFM-Based Non-Parametric Model Enabled Big Data Platform for Predicting Passenger Car Sales in Sustainable Way,
ITS(24), No. 12, December 2023, pp. 16018-16028.
IEEE DOI 2312
BibRef

Qi, Y.X.[Yu-Xin], Wu, J.[Jun], Xu, H.S.[Han-Song], Guizani, M.[Mohsen],
Blockchain Data Mining With Graph Learning: A Survey,
PAMI(46), No. 2, February 2024, pp. 729-748.
IEEE DOI 2401
To analyze system operation and participant behavior. BibRef

Alaminos, D.[David], Salas, M.B.[M. Belén], Partal-Ureña, A.[Antonio],
Hybrid ARMA-GARCH-Neural Networks for intraday strategy exploration in high-frequency trading,
PR(148), 2024, pp. 110139.
Elsevier DOI 2402
High-frequency, Intraday trading, Defence stock prices, FOREX markets, Neural networks, Autoregressive moving average, Quantum computing BibRef

Le, T.[Tan], Reisslein, M.[Martin], Shetty, S.[Sachin],
Multi-Timescale Actor-Critic Learning for Computing Resource Management With Semi-Markov Renewal Process Mobility,
ITS(25), No. 1, January 2024, pp. 452-461.
IEEE DOI 2402
Streaming media, Transcoding, Blockchains, Computational modeling, Resource management, Task analysis, Edge computing, vehicular network BibRef

Liu, R.R.[Rui-Rui], Liu, H.X.[Hao-Xian], Huang, H.[Huichou], Song, B.[Bo], Wu, Q.Y.[Qing-Yao],
Multimodal multiscale dynamic graph convolution networks for stock price prediction,
PR(149), 2024, pp. 110211.
Elsevier DOI 2403
Stock movement prediction, Multimodal feature fusing, Multiscale architecture, Graph convolutional network BibRef

Jiang, Y.C.[Yun-Cheng], Ouyang, B.[Bin], Yan, Z.G.[Zhi-Gang],
Spatial Correlation between the Changes in Supply and Demand for Water-Related Ecosystem Services,
IJGI(13), No. 3, 2024, pp. 68.
DOI Link 2404
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Iliopoulou, P.[Polixeni], Krassanakis, V.[Vassilios], Misthos, L.M.[Loukas-Moysis], Theodoridi, C.[Christina],
A Spatial Regression Model for Predicting Prices of Short-Term Rentals in Athens, Greece,
IJGI(13), No. 3, 2024, pp. 63.
DOI Link 2404
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Rao, K.V.[K. Venkateswara], Reddy, B.V.R.[B. Venkata Ramana],
HM-SMF: An Efficient Strategy Optimization using a Hybrid Machine Learning Model for Stock Market Prediction,
IJIG(24), No. 2, March 2024, pp. 2450013.
DOI Link 2404
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Lu, Y.[Yong], Shu, Z.[Zishan], Li, A.[Anke], Zhang, H.[Huanting],
A Real-Time Forecast Model Based on Convolutional Neural Network and Attention Mechanism for Passenger Car Sales in 5G Environment,
ITS(25), No. 3, March 2024, pp. 2858-2868.
IEEE DOI 2405
Automobiles, Predictive models, Data models, Convolutional neural networks, Computational modeling, forecast model BibRef

Saâdaoui, F.[Foued], Rabbouch, B.[Bochra], Garg, H.[Harish],
Multiresolution causality of Bitcoin on GCC stock markets: Utilizing EMD-Granger analytical methodology,
PRL(181), 2024, pp. 106-112.
Elsevier DOI 2405
Multiresolution pattern recognition, Predictive analytics, Cryptocurrency, GCC economy, Stock markets, Empirical mode decomposition BibRef

Laurent, V.[Vincent], Van, O.V.[Olivier Vo],
Survival Forest for Left-Truncated Right-Censored Data,
IPOL(14), 2024, pp. 194-204.
DOI Link
WWW Link. 2407
Code, Lifetime. Compute lifetime of patient or equipment. BibRef

Saâdaoui, F.[Foued],
Structural self-similarity pattern in global food prices: Utilizing a segmented multifractal detrended fluctuation analysis,
PRL(184), 2024, pp. 74-79.
Elsevier DOI 2408
Multifractal pattern recognition, Commodity market dynamics, Segmented MF-DFA, Food prices BibRef

Varshney, R.P.[Ravi Prakash], Sharma, D.K.[Dilip Kumar],
Enhancing stock market prediction through image encoding, pattern recognition, and ensemble learning with custom error correction techniques,
IJCVR(14), No. 6, 2024, pp. 654-676.
DOI Link 2410
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Wang, J.[Jun], Feng, S.Y.[Si-Yuan], Yang, H.[Hai],
Spatial-Temporal Upfront Pricing Under a Mixed Pooling and Non-Pooling Market With Reinforcement Learning,
ITS(25), No. 11, November 2024, pp. 17628-17649.
IEEE DOI 2411
Pricing, Reinforcement learning, Vehicles, Optimization, Trajectory, Vehicle dynamics, Markov decision processes, reinforcement learning BibRef

Coluccia, A.[Angelo], Fascista, A.[Alessio],
Low-Complexity Prediction of Energy Statistic Exceedance Probability for eta-mu Variates,
SPLetters(31), 2024, pp. 3094-3098.
IEEE DOI 2411
Random variables, Power system reliability, Computational modeling, Tail, Polynomials, Numerical models, cumulant expansion BibRef

Driss, R.[Riane], Widad, E.[Ettazi], Ahmed, E.[Ettalbi],
Optimizing Costs for Cloud-Based Long-Running Activities using ILP,
ISCV24(1-6)
IEEE DOI 2408
Costs, Pricing, Quality of service, Linear programming, Complexity theory, Resource management, Time factors, long-running activities BibRef

Dieguez, T.[Teresa], Loureiro, P.[Paula], Ferreira, I.[Isabel],
The gap between the expectations of Gen Z and Organizations in Industry 4.0,
ISCV24(1-6)
IEEE DOI 2408
Training, Resistance, Technological innovation, Leadership, Statistical analysis, Europe, Companies, Generation Z, skills, upskilling BibRef

Zougari, S.[Soundous], Daoud, M.[Mohamed], Sabri, A.[Abdelouahed], Zougari, A.[Ayoub], Chahboun, A.[Assaad], Azyat, A.[Abdelilah],
Automating the Recognition of Microservices from Business Process Analysis,
ISCV24(1-8)
IEEE DOI 2408
Analytical models, Software architecture, Semantics, Microservice architectures, Clustering algorithms, Dependency Analysis BibRef

Benabou, A.[Adil], Touhami, F.[Fatima], Demraoui, L.[Lamiae],
Artificial Intelligence and the Future of Human Resource Management,
ISCV24(1-8)
IEEE DOI 2408
Training, Ethics, Technological innovation, Sensitivity, Standards organizations, Organizations, Trajectory, HR Transformation BibRef

Hamzaoui, O.[Othmane], Françoise, B.[Brian], Obeid, H.[Hussein], Le Masson, S.[Stéphane], Gualous, H.[Hamid],
Neural Network-Driven Optimization for Cost Minimization in Telecom Energy Systems with Nonlinear Converter Efficiencies,
ISCV24(1-6)
IEEE DOI 2408
Renewable energy sources, Costs, Optimization models, Neural networks, Refining, Data models, Communications technology, Microgrids BibRef

Al, M.A.[Mariam Ait], Achchab, S.[Said], Lahrichi, Y.[Younes],
Hybrid Deep Learning Perspective on Stock Market Liquidity Prediction in the MENA Region,
ISCV24(1-5)
IEEE DOI 2408
Deep learning, Analytical models, Technological innovation, Uncertainty, Biological system modeling, Time series analysis, Hybrid deep learning BibRef

Hachache, R.[Rachida], Bennani, R.[Rachid], Chaoub, A.[Abdelaali], Grilo, A.[António], Tamtaoui, A.[Ahmed], Lakssir, B.[Brahim], Yahyaouy, A.[Ali],
Models for Short-Term Energy Load Forecasting: The Moroccan Cities Case and Dataset,
ISCV24(1-6)
IEEE DOI 2408
Meters, Supply and demand, Electricity, Computational modeling, Biological system modeling, Urban areas, Smart Grids BibRef

Mortaji, M.[Manale], Khiat, A.[Azeddine], Benhouad, M.[Mohamed],
Reinforcement learning application in portfolio optimization: A comprehensive literature review,
ISCV24(1-6)
IEEE DOI 2408
Machine learning algorithms, Terminology, Reviews, Decision making, Deep reinforcement learning, Intelligent agents, artificial intelligence BibRef

Tang, B.[BaoFu], Chang, D.M.[Dong-Meau], Yang, J.J.[Jun-Jie],
Consumer Evaluation Using Machine Learning for the Predictive Analysis of Consumer Purchase Indicators,
IoTDesign24(660-665)
IEEE DOI 2404
Measurement, Filters, Reviews, Machine learning, Search engines, Convolutional neural networks BibRef

Li, X.[Xu], Peng, D.X.[Dong Xu],
Design of zero knowledge proof algorithm for data transaction,
CVIDL23(338-342)
IEEE DOI 2403
Deep learning, Smart contracts, Resists, Blockchains, Fraud, Security, zero-knowledge proof, data transaction, blockchain BibRef

Pathak, P.[Prakrit], Jain, A.[Akash], Bansal, M.[Mohit], Rana, P.S.[Prashant Singh],
SentiNet: Empowering Robust Loan Default Prediction through Ensemble Modeling,
ICCVMI23(1-6)
IEEE DOI 2403
Training, Analytical models, Filtering, Computational modeling, Standardization, Predictive models, Data models, Correlation analysis BibRef

Roy, S.[Shivamshu], Kumar, V.[Vimal], Gupta, U.[Umesh],
Improving Stock Market Forecasting Using Advanced Time Series Analysis Techniques,
ICCVMI23(1-6)
IEEE DOI 2403
Training, Analytical models, Smoothing methods, Time series analysis, Predictive models, ARIMA BibRef

Shah, V.[Vaishvi], Gupta, V.[Vivek], Gandhi, T.[Tushya], Gupta, R.K.[Rajeev Kumar],
Efficient Medical Supply Chain Forecasting Using Time Series Analysis,
ICCVMI23(1-6)
IEEE DOI 2403
Adaptation models, Analytical models, Time series analysis, Supply chains, Medical services, Predictive models, forecasting BibRef

García-Sigüenza, J.[Javier], Vicent, J.F.[José F.], Llorens-Largo, F.[Faraón], Berná-Martínez, J.V.[José-Vicente],
Few-shot Learning for Prediction of Electricity Consumption Patterns,
IbPRIA23(705-715).
Springer DOI 2307
BibRef

Zhu, C.Q.[Chun-Qiang], Zhu, L.[Li], Liu, B.[Bin],
A Prediction Method of Anti-Electricity Stealing Based on Big Data of Electric Power,
ICIVC22(939-945)
IEEE DOI 2301
Training, Support vector machines, Software algorithms, Artificial neural networks, Big Data, Prediction algorithms, MATLAB BibRef

Xiao, Y.F.[Yu-Fan], Pan, Q.P.[Qi-Ping], Li, D.Z.[Deng-Zheng], Deng, F.Q.[Fu-Qin], Feng, Q.[Qi], Yi, N.[Ningbo],
Research on Financial Trading Strategies Based on Dynamic Programming Theory,
ICIVC22(946-951)
IEEE DOI 2301
Gold, Time series analysis, Bitcoin, Dynamic programming, Planning, Resource management, price forecast BibRef

Zhu, L.[Li], Han, K.[Kaiping],
Personalized Access and Cross-Platform Associated Bulk Commodity Trading Entity Inspection,
ICIVC22(952-957)
IEEE DOI 2301
Costs, Process control, Collaboration, Inspection, Collaborative work, Real-time systems, Data models, Bulk commodity, Cross-platform associated BibRef

He, Y.[Yu], Zhou, H.[Hong], Kimm, S.[Simon], Xue, J.[Jiao],
Modeling for Stock Trends: A Study of Two-Stage Pattern Strategy,
ICIVC22(906-912)
IEEE DOI 2301
Image recognition, Shape, Profitability, Predictive models, Turning, Security, Stock trend, Trading rules BibRef

Hillebrand, L.[Lars], Deußer, T.[Tobias], Dilmaghani, T.[Tim], Kliem, B.[Bernd], Loitz, R.[Rüdiger], Bauckhage, C.[Christian], Sifa, R.[Rafet],
KPI-BERT: A Joint Named Entity Recognition and Relation Extraction Model for Financial Reports,
ICPR22(606-612)
IEEE DOI 2212
Recurrent neural networks, Filtering, Key performance indicator, Bit error rate, Companies, Tagging, Transformers BibRef

Alsalemi, A.[Abdullah], Amira, A.[Abbes], Malekmohamadi, H.[Hossein], Diao, K.[Kegong],
Creating 3D Gramian Angular Field Representations for Higher Performance Energy Data Classification,
ICIP22(3586-3590)
IEEE DOI 2211
Energy consumption, Image edge detection, Data visualization, Fires, Transforms, Gramian angular field, energy efficiency BibRef

Youness, J.[Jouilil], Driss, M.[Mentagui],
An ARIMA Model for Modeling and Forecasting the Dynamic of Univariate Time Series: The case of Moroccan Inflation Rate,
ISCV22(1-5)
IEEE DOI 2208
Economics, Adaptation models, Machine learning algorithms, Computational modeling, Time series analysis, Predictive models, Morocco. BibRef

Mourad, Z.[Zbakh], Noura, A.[Aknin], Mohamed, C.[Chrayah],
Towards a new method for classifying employee performance using machine learning algorithms,
ISCV22(1-5)
IEEE DOI 2208
Productivity, Analytical models, Machine learning algorithms, Social networking (online), Profitability, Companies, Principal Component Analysis BibRef

Ourdani, N.[Nabil], Chrayah, M.[Mohamed],
Big Data and public finance sector,
ISCV22(1-6)
IEEE DOI 2208
Decision making, Machine learning, Big Data, Intelligent systems, Public finance, Big Data, Decision making BibRef

Bounid, S.[Samira], Oughanem, M.[Mohammed], Bourkadi, S.[Salman],
Advanced Financial Data Processing and Labeling Methods for Machine Learning,
ISCV22(1-6)
IEEE DOI 2208
Machine learning algorithms, Machine learning, Predictive models, Prediction algorithms, Labeling, Stock markets, Forecasting, triple barrier BibRef

Hanine, Y.[Yahya], Malick, M.E.[Mohamed El_Moktar], Tkiouat, M.[Mohamed], Lahrichi, Y.[Younes], Alaoui, Y.L.[Youssef Lamrani],
A New Financial Group Lending Based on Smart Contracts: An Agent-based Simulation,
ISCV22(1-5)
IEEE DOI 2208
Codes, Computational modeling, Smart contracts, Finance, Delays, Blockchains, component, formatting, style, styling, insert BibRef

Imane, M.[Mjimer], Aoula, E.S.[Es-Saadia], Achouyab, E.[El_Hassan],
Using Support Vector Regression to Predict the Overall Equipment Effectiveness Indicator*,
ISCV22(1-5)
IEEE DOI 2208
Support vector machines, Training, Computational modeling, Supervised learning, Supervised Learning BibRef

Fobi, S.[Simone], Mugyenyi, J.[Joel], Williams, N.J.[Nathaniel J.], Modi, V.[Vijay], Taneja, J.[Jay],
Predicting Levels of Household Electricity Consumption in Low-Access Settings,
WACV22(2213-2222)
IEEE DOI 2202
Training, Image segmentation, Satellites, Aggregates, Buildings, Power industry, Semi- and Un- supervised Learning BibRef

Zhang, L.[Lelin], Nan, X.[Xi], Huang, E.[Eva], Liu, S.[Sidong],
Social E-commerce Tax Evasion Detection Using Multi-modal Deep Neural Networks,
DICTA21(01-06)
IEEE DOI 2201
Deep learning, Sensitivity, Social networking (online), Digital images, Computational modeling, Neural networks, deep neural networks BibRef

Kim, J.[Jaechul], Dai, X.Y.[Xiao-Yan], Hsieh, Y.[Yisan], Tanimoto, H.[Hiroki], Fujivoshi, H.[Hironobu],
Cut and paste curriculum learning with hard negative mining for point-of-sale systems,
MVA21(1-5)
DOI Link 2109
Training, Learning systems, Automation, Machine learning, Real-time systems, Data models BibRef

Cahill, J.[Joan], Howard, V.[Vivienne], Huang, Y.F.[Yu-Fei], Ye, J.C.[Jun-Chi], Ralph, S.[Stephen], Dillon, A.[Aidan],
Addressing Human Factors and Ethics in the Design of 'Future Work' and Intelligent Systems for Use in Financial Services - Person Centered Operations, Intelligent Work and the Triple Bottom Line,
DHM21(I:3-13).
Springer DOI 2108
BibRef

Tran, D.T.[Dat Thanh], Kanniainen, J.H.[Ju-Ho], Gabbouj, M.[Moncef], Iosifidis, A.[Alexandros],
Data Normalization for Bilinear Structures in High-Frequency Financial Time-series,
ICPR21(7287-7292)
IEEE DOI 2105
Time series analysis, Focusing, Noise measurement, Forecasting BibRef

Ye, J.X.[Jie-Xia], Zhao, J.J.[Juan-Juan], Ye, K.J.[Ke-Jiang], Xu, C.Z.[Cheng-Zhong],
Multi-Graph Convolutional Network for Relationship-Driven Stock Movement Prediction,
ICPR21(6702-6709)
IEEE DOI 2105
Deep learning, Adaptation models, Logic gates, Feature extraction, Encoding, Indexes, GCN, Stock Price BibRef

Han, L.[Liang], Yin, Z.Z.[Zhao-Zheng], Xia, Z.[Zhurong], Guo, L.[Li], Tang, M.Q.[Ming-Qian], Jin, R.[Rong],
Price Suggestion for Online Second-hand Items,
ICPR21(5920-5927)
IEEE DOI 2105
Pricing, price suggestion system, online second-hand item, truncate loss BibRef

Pavlidis, G.[George], Tsolakis, A.C.[Apostolos C.], Ioannidis, D.[Dimosthenis], Tzovaras, D.[Dimitrios],
Demand Flexibility Estimation Based on Habitual Behaviour and Motif Detection,
PRAConBE20(417-431).
Springer DOI 2103
Power consumption and production. BibRef

Tian, H.Y.[Hong-Yun],
Research Hotspots Analysis of E-commerce Security in China,
CVIDL20(468-471)
IEEE DOI 2102
electronic commerce, pattern clustering, security of data, statistical analysis, e-commerce security, co-word analysis, Research hotspots BibRef

Duan, X., Li, J., Chen, Y.,
Analysis of Amazon Market Product Satisfaction Based on LDA Theme Model,
CVIDL20(693-696)
IEEE DOI 2102
customer satisfaction, electronic commerce, grey systems, linear discriminant analysis, principal component analysis, Grey correlation degree BibRef

Huang, W., Huang, W., Cai, D.,
Finding EFL and EQL Allocations of Indivisible Goods,
CVIDL20(448-452)
IEEE DOI 2102
computational complexity, economics, Pareto optimisation, resource allocation, EQ, approximate fair allocation, Optimal allocation BibRef

Zheng, X., Sang, Z.X., Yang, M.,
The Health Index Methodology of Integrated Energy System,
CVIDL20(426-430)
IEEE DOI 2102
distribution networks, power apparatus, power grids, single equipment components, high monomer value, knowledge asset BibRef

Li, X., Ding, Y., He, X., Shi, L., Xu, H.,
Application and research of enterprise level contract system based on localization platform,
CVIDL20(683-687)
IEEE DOI 2102
architecture, construction industry, contracts, design engineering, information technology, project management, recycling, requirement analysis BibRef

peng, L.,
Online Personal Credit System Design Based on Public Block Chains,
CVIDL20(546-549)
IEEE DOI 2102
electronic money, Internet, Internet technology, conventional offline channels, cross-border online transaction, public block chains BibRef

Lamsaddak, K., Mentagui, D.,
Multi-agent simulation of the Moroccan conventional insurance sector,
ISCV20(1-7)
IEEE DOI 2011
computer simulation, insurance, insurance data processing, multi-agent systems, risk management, socio-economic effects, multi-agent simulation BibRef

Mónica, R., Henry, Q., Estela, M., Washington, F.,
Why implement continuity plans in Organizations? Approach of a prospective study based on ITIL,
ISCV20(1-5)
IEEE DOI 2011
business continuity, organisational aspects, organizations, ITIL V3, business continuity plan, history, life cycle, BCP, Companies, Recovery BibRef

Vasquez, E.J., Ortega, J.C.,
Design of a business contingency plan. Case study: Municipality of Cantón Suscal.,
ISCV20(1-10)
IEEE DOI 2011
business continuity, business data processing, information technology, risk analysis, business contingency plan, TIC BibRef

Amdah, L., Anwar, A.,
A DSL for collaborative Business Process,
ISCV20(1-6)
IEEE DOI 2011
business data processing, business process re-engineering, groupware, Unified Modeling Language, visual languages, BPMN, DSL, Collaborative Business Process BibRef

Mahiri, F., Najoua, A., Souda, S.B.,
Data-driven sustainable smart manufacturing: A conceptual framework,
ISCV20(1-7)
IEEE DOI 2011
Big Data, cloud computing, data analysis, manufacturing systems, product life cycle management, product lifecycle BibRef

Sridhar, S., Mootha, S., Subramanian, S.,
Detection of Market Manipulation using Ensemble Neural Networks,
ISCV20(1-8)
IEEE DOI 2011
learning (artificial intelligence), neural nets, stock markets, stock market, market manipulation, manipulation scenarios, Market Manipulation BibRef

El Hlouli, F.Z., Riffi, J., Mahraz, M.A., El Yahyaouy, A., Tairi, H.,
Credit Card Fraud Detection Based on Multilayer Perceptron and Extreme Learning Machine Architectures,
ISCV20(1-5)
IEEE DOI 2011
bank data processing, credit transactions, data mining, feedforward neural nets, fraud, mobile commerce, ELM BibRef

Zhai, W.,
Research on the Audit Failure Based on the Perspective of Manager Behavior Game,
ICIVC20(307-311)
IEEE DOI 2009
Economics, Games, Game theory, Analytical models, Law, Companies, Industries, udit failure, stimulation, punishment, game theory analysis BibRef

Tobin, T.[Turner], Kashef, R.[Rasha],
Efficient Prediction of Gold Prices Using Hybrid Deep Learning,
ICIAR20(II:118-129).
Springer DOI 2007
BibRef

Dick, K., Charih, F., Woo, J., Green, J.R.,
Gas Prices of America: The Machine-Augmented Crowd-Sourcing Era,
CRV20(158-165)
IEEE DOI 2006
dataset preparation, remote sensing, character recognition BibRef

Kamara-Esteban, O.[Oihane], Borges, C.E.[Cruz E.], Casado-Mansilla, D.[Diego],
Can I Shift My Load? Optimizing the Selection of the Best Electrical Tariff for Tertiary Buildings,
CVS19(658-669).
Springer DOI 1912
BibRef

Arevalillo, J.M.[Jorge M.],
Model Based Recursive Partitioning for Customized Price Optimization Analytics,
IbPRIA19(I:113-124).
Springer DOI 1910
BibRef

Cheng, D., Niu, Z., Tu, Y., Zhang, L.,
Prediction Defaults for Networked-guarantee Loans,
ICPR18(361-366)
IEEE DOI 1812
Predictive models, Contracts, Training, Feature extraction, Prediction algorithms, Economics BibRef

wang, X., Li, P., Hawbani, A.,
An Efficient Budget Allocation Algorithm for Multi-Channel Advertising,
ICPR18(886-891)
IEEE DOI 1812
Resource management, Advertising, Decision making, Optimization, Space exploration, Approximation algorithms, reinforcement learning BibRef

Tsang, G., Deng, J., Xie, X.,
Recurrent Neural Networks for Financial Time-Series Modelling,
ICPR18(892-897)
IEEE DOI 1812
Wavelet transforms, Hidden Markov models, Predictive models, Logic gates, Time series analysis, Indexes, Support vector machines BibRef

Nabil, M., Ismail, M., Mahmoud, M., Shahin, M., Qaraqe, K., Serpedin, E.,
Deep Recurrent Electricity Theft Detection in AMI Networks with Random Tuning of Hyper-parameters,
ICPR18(740-745)
IEEE DOI 1812
Detectors, Energy consumption, Computer crime, Training, Smart meters, Support vector machines, Data models, deep machine learning BibRef

Luo, Z., Chen, J., Cai, X.J., Tanaka, K., Takiguchi, T., Kinkyo, T., Hamori, S.,
Oil Price Forecasting Using Supervised GANs with Continuous Wavelet Transform Features,
ICPR18(830-835)
IEEE DOI 1812
Oils, Continuous wavelet transforms, Forecasting, Predictive models BibRef

Karpio, K.[Krzysztof], Lukasiewicz, P.[Piotr],
Pattern Recognition in Financial Data Using Association Rule,
ICCVG18(512-521).
Springer DOI 1810
BibRef

Cui, L.X.[Li-Xin], Bai, L.[Lu], Rossi, L.[Luca], Zhang, Z.H.[Zhi-Hong], Jiao, Y.H.[Yu-Hang], Hancock, E.R.[Edwin R.],
A Preliminary Survey of Analyzing Dynamic Time-Varying Financial Networks Using Graph Kernels,
SSSPR18(237-247).
Springer DOI 1810
BibRef

Jiao, Y.H.[Yu-Hang], Cui, L.X.[Li-Xin], Bai, L.[Lu], Wang, Y.[Yue],
Analyzing Time Series from Chinese Financial Market Using a Linear-Time Graph Kernel,
SSSPR18(227-236).
Springer DOI 1810
BibRef

Mouhib, N., Bah, S., Berrado, A.,
The viable system model driven the organization and the information system design,
ISCV18(1-6)
IEEE DOI 1807
project management, software development management, software engineering, VSM, information system design, Viable System Model BibRef

Benany, E., Beqqali, E.,
Choreography for interoperability in the e-Government applications,
ISCV18(1-4)
IEEE DOI 1807
Web services, XML, government data processing, open systems, Web services, XML specification, business process engines, e-Government BibRef

Sellamy, K., Fakhri, Y., Boulaknadel, S., Moumen, A., Hafed, K., Jamil, H., Lakhrissi, Y.,
Web mining techniques and applications: Literature review and a proposal approach to improve performance of employment for young graduate in Morocco,
ISCV18(1-5)
IEEE DOI 1807
Internet, data mining, algorithms, commercial information, literature review, web data mining, web pages, Java, Linux, Tools, web usages mining BibRef

Lamghari, Z., Radgui, M., Saidi, R., Rahmani, M.D.,
A set of indicators for BPM life cycle improvement,
ISCV18(1-8)
IEEE DOI 1807
business data processing, business process re-engineering, data mining, BPIM, BPM life cycle improvement, Process Mining BibRef

Bessane, S.F., Camara, M.S., Fall, I., Bah, A.,
Causal model of performance measurement systems by combining qualitative and quantitative models for robust results,
ISCV18(1-7)
IEEE DOI 1807
business data processing, data acquisition, innovation management, SMP, causal model, data collection, quantitative BibRef

El Hachami, K., Tkiouat, M.,
An approach for modeling the economy as a complex system using agent-based theory,
ISCV18(1-6)
IEEE DOI 1807
economics, multi-agent systems, agent-based theory, complex system, economic activities, economic agents, economic changes, interactions BibRef

Alaoui, Y.L., Tkiouat, M.,
Developing a decision making support tool for planning customer satisfaction strategies in microfinance industry,
ISCV18(1-7)
IEEE DOI 1807
belief networks, customer satisfaction, decision making, decision support systems, stock markets, Bayesian networks, MFI, Microfinance institutions BibRef

Elsaid, H., Thomas, G., Williams, D.,
Texture features based on the use of the hough transform and income inequality metrics,
IPTA17(1-6)
IEEE DOI 1804
Hough transforms, feature extraction, image classification, image colour analysis, image segmentation, image texture, income inequality BibRef

Siew, L.W.[Lam Weng], Wai, C.J.[Chen Jia], Hoe, L.W.[Lam Weng],
Data Driven Decision Analysis in Bank Financial Management with Goal Programming Model,
IVIC17(681-689).
Springer DOI 1711
BibRef

Ghosh, I.[Indranil], Sanyal, M.K.[Manas K.], Jana, R.K.,
Analysis of Causal Interactions and Predictive Modelling of Financial Markets Using Econometric Methods, Maximal Overlap Discrete Wavelet Transformation and Machine Learning: A Study in Asian Context,
PReMI17(664-672).
Springer DOI 1711
BibRef

Chen, Z.Y.[Zhi-Yuan], Khoa, L.D.V.[Le Dinh Van], Boon, L.S.[Lee Soon],
A Hybrid Model of Differential Evolution with Neural Network on Lag Time Selection for Agricultural Price Time Series Forecasting,
IVIC17(155-167).
Springer DOI 1711
BibRef

Jumin, J.[Johnlee], Ijab, M.T.[Mohamad Taha], Zaman, H.B.[Halimah Badioze],
An Integrated Social Media Trading Platform for B40 Social Media Entrepreneurship,
IVIC17(112-119).
Springer DOI 1711
BibRef

Hoe, L.W.[Lam Weng], Siew, L.W.[Lam Weng], Fai, L.K.[Liew Kah],
Improvement on the Efficiency of Technology Companies in Malaysia with Data Envelopment Analysis Model,
IVIC17(19-30).
Springer DOI 1711
BibRef

Ya'acob, S.[Suraya], Ali, N.M.[Nazlena Mohamad], Liang, H.N.[Hai-Ning], Zainuddin, N.M.[Norziha Megat], Nayan, N.S.M.[Nor Shita Mat],
Visualization Principles for Facilitating Strategy Development Process in the Organization,
IVIC17(31-42).
Springer DOI 1711
BibRef

Akkiyat, I.[Ikram], Souissi, N.[Nissrine],
Improvement view: Extension of seven views approach,
ISCV17(1-5)
IEEE DOI 1710
Biological system modeling, Data models, Organizations, Stakeholders, BPM, Intelligent cycle, PDCA, Process improvement, Seven Views BibRef

Chouiekh, A., Haj, E.H.I.E.,
Machine learning techniques applied to prepaid subscribers: Case study on the telecom industry of Morocco,
ISCV17(1-8)
IEEE DOI 1710
Boosting, Classification algorithms, Feature extraction, BibRef

Daghouri, A., Mansouri, K., Qbadou, M.,
Towards a decision support system, based on the systemic and multi-agent approaches for organizational performance evaluation of a risk management unit: Banks case,
ISCV17(1-8)
IEEE DOI 1710
Banking, Decision making, Decision support systems, Organizations, Risk management, Unified modeling language, Organizational performance, Systemic, thinking BibRef

El Hajjami, S.[Salma], Berrada, M.[Mohammed], Harti, M.[Mostafa], Diallo, G.[Gayo],
Towards an agent-based approach for multidimensional analyses of semantic web data,
ISCV17(1-6)
IEEE DOI 1710
competitive intelligence, multi-agent systems. BibRef

Ikrame, B., Aziza, A., Mourad, P.O.,
Customer experience in a regulated telecom market from mobile service users perspective,
ISCV17(1-8)
IEEE DOI 1710
mobile communication, statistical analysis, BibRef

McCluskey, J., Liu, J.G.[Jian-Guo],
US financial market forecasting using data classification with features from global markets,
ICIVC17(965-969)
IEEE DOI 1708
Predictive models, NASDAQ, data classification, financial market forecasting, gradient boosting, support, vector, machines BibRef

Yang, W.D.[Wen-Dong], Lou, Z.Z.[Zheng-Zheng], Ji, B.[Bo],
A multi-factor analysis model of quantitative investment based on GA and SVM,
ICIVC17(1152-1155)
IEEE DOI 1708
Genetic algorithms, Prediction algorithms, Predictive models, Support vector machines, GA, SVM, feature weighting, investment, multi-factor, model BibRef

Yu, Y.W.[Ya-Wen], Wang, S.S.[Shan-Shan], Zhang, L.J.[Li-Jun],
Stock price forecasting based on BP neural network model of network public opinion,
ICIVC17(1058-1062)
IEEE DOI 1708
Analytical models, Forecasting, Internet, Investment, Training, BP neural network, network public opinion, stock price forecast, text, analysis BibRef

Zeng, J.Y.[Jun-Ya], Lin, J.B.[Jian-Bang], Wang, T.[Tian],
A new competing risks model for predicting prepayment and default using data mining,
ICIVC17(985-989)
IEEE DOI 1708
Testing, Training, competing risks model, data mining, default, logistic regression, microfinance, prepayment BibRef

Cui, L.X.[Li-Xin], Bai, L.[Lu], Wang, Y.[Yue], Bai, X.[Xiao], Zhang, Z.H.[Zhi-Hong], Hancock, E.R.[Edwin R.],
P2P Lending Analysis Using the Most Relevant Graph-Based Features,
SSSPR16(3-14).
Springer DOI 1611
BibRef

Pinheiro do Nascimento, T., Labidi, S., Neto, P.B., Timbó, N., Almeida, A.,
A system based on genetic algorithms as a decision making support for the purchase and sale of assets at Sao Paulo Stock Exchange,
ICCVIA15(1-6)
IEEE DOI 1603
decision making BibRef

Yang, F.[Fan], Zhang, J.J.[Jiang-Jun],
Bullish-bearish-based neural network stock trading decision supportano its application in Hong Kong stock market,
ICWAPR15(179-184)
IEEE DOI 1511
generalisation (artificial intelligence) BibRef

Dhamotharan, L., Ismail, M.T., Ignatius, J., Xue, P.X.[Peng-Xiang],
Exchange rate and interest rate differential: A conundrum re-examined via wavelet analysis,
ICWAPR15(75-80)
IEEE DOI 1511
discrete wavelet transforms BibRef

Podsiadlo, M.[Mariusz], Rybinski, H.[Henryk],
Application of Fuzzy Rough Sets to Financial Time Series Forecasting,
PReMI15(397-406).
Springer DOI 1511
BibRef

Letchford, A.[Adrian], Gao, J.B.[Jun-Bin], Zheng, L.H.[Li-Hong],
Smoothing Security Prices,
ICPR14(1037-1042)
IEEE DOI 1412
Correlation BibRef

Becerra-Gaviño, G.[Gustavo], Barbosa-Santillán, L.I.[Liliana Ibeth],
Neuro-Fuzzy Data Mining Mexico's Economic Data,
CIARP14(645-657).
Springer DOI 1411
BibRef

Ramírez, C.[Cristián], Acuña, G.[Gonzalo],
Forecasting Cash Demand in ATM Using Neural Networks and Least Square Support Vector Machine,
CIARP11(515-522).
Springer DOI 1111
BibRef

Hossain, A.[Altaf], Zaman, F.[Faisal], Nasser, M., Islam, M.M.[M. Mufakhkharul],
Comparison of GARCH, Neural Network and Support Vector Machine in Financial Time Series Prediction,
PReMI09(597-602).
Springer DOI 0912
BibRef

Yang, Q.[Qi], Gan, X.Y.[Xiao-Yu], Li, J.L.[Jian-Long], Yang, F.[Feng],
Simulation of Urbanization Development Using Cellular Automata Model to Inform Urban Planning Policy in Zhangjagang Region, China,
CISP09(1-5).
IEEE DOI 0910
BibRef

Huang, Q.H.[Qing-Hua], Lu, M.H.[Min-Hua],
Evolutionary Discovery of Co-Movement Patterns Among Foreign Currencies,
CISP09(1-5).
IEEE DOI 0910
BibRef

Kajdanowicz, T.[Tomasz], Kazienko, P.[Przemyslaw],
Prediction of Sequential Values for Debt Recovery,
CIARP09(337-344).
Springer DOI 0911
BibRef

Nakajima, T.[Tatsuo], Kimura, H.[Hiroaki], Yamabe, T.[Tetsuo], Lehdonvirta, V.[Vili], Takayama, C.[Chihiro], Shiraishi, M.[Miyuki], Washio, Y.[Yasuyuki],
Using Aesthetic and Empathetic Expressions to Motivate Desirable Lifestyle,
SSC08(220-234).
Springer DOI 0810
BibRef

Zhao, H.V.[H. Vicky], Lin, W.S.[W. Sabrina], Liu, K.J.R.[K. J. Ray],
Game-theoretic analysis of maximum-payoff multiuser collusion,
ICIP08(1276-1279).
IEEE DOI 0810
BibRef

Bicego, M.[Manuele], oGrosso, E.[Enrico], Otranto, E.[Edoardo],
A Hidden Markov Model Approach to Classify and Predict the Sign of Financial Local Trends,
SSPR08(852-861).
Springer DOI 0812
BibRef

Jun, T.[Tang],
A Peer Dataset Comparison Outlier Detection Model Applied to Financial Surveillance,
ICPR06(IV: 900-903).
IEEE DOI 0609
BibRef

Chapter on New Unsorted Entries, and Other Miscellaneous Papers continues in
Time Series Analysis, One-D Waveform Analysis, One-D Signals .