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Forecasting of global horizontal irradiance by exponential smoothing, using decompositions
Yang, Dazhi; Sharma, Vishal; Ye, Zhen; Lim, Lihong Idris; … - In: Energy 81 (2015) C, pp. 111-119
Time series methods are frequently used in solar irradiance forecasting when two dimensional cloud information provided by satellite or sky camera is unavailable. ETS (exponential smoothing) has received extensive attention in the recent years since the invention of its state space formulation....
Persistent link: https://www.econbiz.de/10011209512
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Multi-source model of heterogeneous data analysis for oil price forecasting
Baboshkin, Pavel; Uandykova, Mafura - In: International Journal of Energy Economics and Policy : IJEEP 11 (2021) 2, pp. 384-391
Persistent link: https://www.econbiz.de/10012616117
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Assessing asset tail risk with artificial intelligence : the application of artificial neural network
Becker, Ying L.; Guo, Lin; Nurmamatov, Odilbek - In: Advances in Pacific Basin business, economics, and finance 8 (2020), pp. 23-52
Persistent link: https://www.econbiz.de/10012601378
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Artificial neural network base short-term electricity load forecasting : a case study of a 132/33kv transmission sub-station
Samuel, Isaac Adekunle; Ekundayo, Segun; Awelewa, Ayokunle - In: International Journal of Energy Economics and Policy : IJEEP 10 (2020) 2, pp. 200-205
Persistent link: https://www.econbiz.de/10012484536
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Prediction of Iran's renewable energy generation in the fifth development plan
Chaharsooghi, S. Kamal; Rezaei, Mohsen - In: International journal of services and operations management 25 (2016) 1, pp. 120-133
Persistent link: https://www.econbiz.de/10011593496
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Next-day Bitcoin price forecast
Munim, Ziaul Haque; Shakil, Mohammad Hassan; Alon, Ilan - In: Journal of risk and financial management : JRFM 12 (2019) 2/103, pp. 1-15
network autoregression (NNAR) models. Employing the static forecast approach, we forecast next-day Bitcoin price both with and … without re-estimation of the forecast model for each step. For cross-validation of forecast results, we consider two different …-sample forecast periods. The Diebold Mariano test confirms the superiority of forecast results of ARIMA model over NNAR in the test …
Persistent link: https://www.econbiz.de/10012021953
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Optimum prediction and forecasting of wheat demand in Iran
Babazadeh, Reza; Shamsi, Meisam; Shafipour, Fatemeh - In: International journal of applied management science : IJAMS 13 (2021) 2, pp. 141-151
Persistent link: https://www.econbiz.de/10012594613
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Forecasting stock market realized volatility using random forest and artificial neural network in South Africa
Diane, Lamine; Brijlal, Pradeep - In: International journal of economics and financial issues … 14 (2024) 2, pp. 5-14
Persistent link: https://www.econbiz.de/10014581568
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Machine learning in energy economics and finance: a review
Ghoddusi, Hamed; Creamer Guillén, Germán; Rafizadeh, Nima - In: Energy economics 81 (2019), pp. 709-727
Persistent link: https://www.econbiz.de/10012172954
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A cross-sectional machine learning approach for hedge fund return prediction and selection
Wu, Wenbo; Chen, Jiaqi; Yang, Zhibin; Tindall, Michael L. - In: Management science : journal of the Institute for … 67 (2021) 7, pp. 4577-4601
Persistent link: https://www.econbiz.de/10012624639