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An investigation of model selection criteria for neural network time series forecasting

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  1. Loutfi, Ahmad Amine & Sun, Mengtao & Loutfi, Ijlal & Solibakke, Per Bjarte, 2022. "Empirical study of day-ahead electricity spot-price forecasting: Insights into a novel loss function for training neural networks," Applied Energy, Elsevier, vol. 319(C).
  2. Sen Cheong Kon & Lindsay W. Turner, 2005. "Neural Network Forecasting of Tourism Demand," Tourism Economics, , vol. 11(3), pages 301-328, September.
  3. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
  4. Ediger, Volkan S. & Akar, Sertac & Ugurlu, Berkin, 2006. "Forecasting production of fossil fuel sources in Turkey using a comparative regression and ARIMA model," Energy Policy, Elsevier, vol. 34(18), pages 3836-3846, December.
  5. Linying Yang & Teng Zhang & Peter Glynn & David Scheinker, 2021. "The development and deployment of a model for hospital-level COVID-19 associated patient demand intervals from consistent estimators (DICE)," Health Care Management Science, Springer, vol. 24(2), pages 375-401, June.
  6. Hamid, Shaikh A. & Iqbal, Zahid, 2004. "Using neural networks for forecasting volatility of S&P 500 Index futures prices," Journal of Business Research, Elsevier, vol. 57(10), pages 1116-1125, October.
  7. Shifei Yuan & Hongjie Wu & Chengliang Yin, 2013. "State of Charge Estimation Using the Extended Kalman Filter for Battery Management Systems Based on the ARX Battery Model," Energies, MDPI, vol. 6(1), pages 1-27, January.
  8. Lazrak, Amine & Leconte, Antoine & Chèze, David & Fraisse, Gilles & Papillon, Philippe & Souyri, Bernard, 2015. "Numerical and experimental results of a novel and generic methodology for energy performance evaluation of thermal systems using renewable energies," Applied Energy, Elsevier, vol. 158(C), pages 142-156.
  9. Crone, Sven F. & Hibon, Michèle & Nikolopoulos, Konstantinos, 2011. "Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction," International Journal of Forecasting, Elsevier, vol. 27(3), pages 635-660.
  10. Gary Madden & Joachim Tan, 2008. "Forecasting international bandwidth capacity using linear and ANN methods," Applied Economics, Taylor & Francis Journals, vol. 40(14), pages 1775-1787.
  11. Rossetti Renato, 2019. "Forecasting the Sales of Console Games for the Italian Market," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 23(3), pages 76-88, September.
  12. Muhammad Dawood & Atta-ur Rahman & Sami Ullah & Shakeel Mahmood & Ghani Rahman & Kamran Azam, 2020. "Spatio-statistical analysis of rainfall fluctuation, anomaly and trend in the Hindu Kush region using ARIMA approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 101(2), pages 449-464, March.
  13. Muhammad Nadim Hanif & Khurrum S. Mughal & Javed Iqbal, 2018. "A Thick ANN Model for Forecasting Inflation," SBP Working Paper Series 99, State Bank of Pakistan, Research Department.
  14. Shangkun Deng & Chenguang Wang & Zhe Fu & Mingyue Wang, 2021. "An Intelligent System for Insider Trading Identification in Chinese Security Market," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 593-616, February.
  15. Hanns de la Fuente-Mella & Claudio Elórtegui-Gómez & Benito Umaña-Hermosilla & Marisela Fonseca-Fuentes & Gonzalo Ríos-Vásquez, 2023. "Stochastic Approaches Systems to Predictive and Modeling Chilean Wildfires," Mathematics, MDPI, vol. 11(20), pages 1-23, October.
  16. Dan Lou & Yuehan Yang, 2025. "Joint estimation of transfer learning on time series data," Statistical Papers, Springer, vol. 66(1), pages 1-19, January.
  17. Huang, Chuangxia & Cai, Yaqian & Yang, Xiaoguang & Deng, Yanchen & Yang, Xin, 2023. "Laplacian-energy-like measure: Does it improve the Cross-Sectional Absolute Deviation herding model?," Economic Modelling, Elsevier, vol. 127(C).
  18. Lazrak, Amine & Boudehenn, François & Bonnot, Sylvain & Fraisse, Gilles & Leconte, Antoine & Papillon, Philippe & Souyri, Bernard, 2016. "Development of a dynamic artificial neural network model of an absorption chiller and its experimental validation," Renewable Energy, Elsevier, vol. 86(C), pages 1009-1022.
  19. Emil Kraft & Dogan Keles & Wolf Fichtner, 2020. "Modeling of frequency containment reserve prices with econometrics and artificial intelligence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1179-1197, December.
  20. Lin, Yao-San & Li, Der-Chiang, 2010. "The Generalized-Trend-Diffusion modeling algorithm for small data sets in the early stages of manufacturing systems," European Journal of Operational Research, Elsevier, vol. 207(1), pages 121-130, November.
  21. Tortum, Ahmet & Yayla, Nadir & Çelik, Cafer & Gökdağ, Mahir, 2007. "The investigation of model selection criteria in artificial neural networks by the Taguchi method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 446-468.
  22. Cem Kadilar & Muammer Simsek & Cagdas Hakan Aladag, 2009. "Forecasting The Exchange Rate Series With Ann: The Case Of Turkey," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 9(1), pages 17-29, May.
  23. Zubair Ahmad & Zahra Almaspoor & Faridoon Khan & Mahmoud El-Morshedy, 2022. "On Predictive Modeling Using a New Flexible Weibull Distribution and Machine Learning Approach: Analyzing the COVID-19 Data," Mathematics, MDPI, vol. 10(11), pages 1-26, May.
  24. Iman Fatehi & Bahman Amiri & Afshin Alizadeh & Jan Adamowski, 2015. "Modeling the Relationship between Catchment Attributes and In-stream Water Quality," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5055-5072, November.
  25. Miriyala, Srinivas Soumitri & Subramanian, Venkat & Mitra, Kishalay, 2018. "TRANSFORM-ANN for online optimization of complex industrial processes: Casting process as case study," European Journal of Operational Research, Elsevier, vol. 264(1), pages 294-309.
  26. Yingjun Shen & Taohong Wang & Zhe Song, 2024. "Online performance and proactive maintenance assessment of data driven prediction models," Journal of Intelligent Manufacturing, Springer, vol. 35(8), pages 3959-3993, December.
  27. Dereje Birhanu & Hyeonjun Kim & Cheolhee Jang & Sanghyun Park, 2018. "Does the Complexity of Evapotranspiration and Hydrological Models Enhance Robustness?," Sustainability, MDPI, vol. 10(8), pages 1-34, August.
  28. Ediger, Volkan S. & Akar, Sertac, 2007. "ARIMA forecasting of primary energy demand by fuel in Turkey," Energy Policy, Elsevier, vol. 35(3), pages 1701-1708, March.
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