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Data-driven analysis of the real-time electricity price considering wind power effect
Yang, Shengjie; Xu, Xuesong; Liu, Jiangang; Jiang, Weijin - In: Energy reports 6 (2020) 2, pp. 452-459
market and improve future strategies. However, most of the forecast models eliminate the details to reduce the structural …
Persistent link: https://www.econbiz.de/10012181064
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Forecasting tourism demand using the trend models method : evidence from Indonesia
Kusumastuti, Henni; Novalia; Anum, Adelina - In: The future opportunities and challenges of business in …, (pp. 112-115). 2020
Persistent link: https://www.econbiz.de/10012311123
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Forecasting residential electric power consumption for Bogotá Colombia using regression models
Peña-Guzmán, Carlos; Rey, Juliana - In: Energy reports 6 (2020) 1, pp. 561-566
This study presents three models of multiple linear regressions for forecasting energy demand. The first is a simple multiple linear regression, the second model has an economic interpretation of coefficients (econometric), while the third model is developed in the form of double logarithm...
Persistent link: https://www.econbiz.de/10012177360
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Forecasting with a hybrid method utilizing data smoothing, a variation of the Theta method and shrinkage of seasonal factors
Spiliotis, Evangelos; Assimakopoulos, V.; Nikolopoulos, … - In: International journal of production economics 209 (2019), pp. 92-102
Persistent link: https://www.econbiz.de/10012013066
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Improving food supply chain using hybrid semiparametric regression model
Arunraj, Nari Sivanandam; Ahrens, Diane - In: Supply Management Research : aktuelle …, (pp. 213-238). 2017
Persistent link: https://www.econbiz.de/10011590529
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Editorial: Causality, prediction, and specification analysis : recent advances and future directions
Chen, Xiaohong; Swanson, Norman R. - In: Journal of econometrics 182 (2014) 1, pp. 1-4
Persistent link: https://www.econbiz.de/10010497154
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Characterizing financial crisis by means of the three states random field Ising model
Murota, Mitsuaki; Inoue, Jun-ichi - In: Econophysics of agent-based models, (pp. 83-98). 2014
Persistent link: https://www.econbiz.de/10011281725
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Comparison of deep learning models for multivariate prediction of time series wind power generation and temperature
Mishra, Sambeet; Bordin, Chiara; Taharaguchi, Kota; … - In: Energy reports 6 (2020) 3, pp. 273-286
Wind power experienced a substantial growth over the past decade especially because it has been seen as one of the best ways towards meeting climate change and emissions targets by many countries. Since wind power is not fully dispatchable, the accuracy of wind forecasts is a key element for the...
Persistent link: https://www.econbiz.de/10012183091
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Automatic identification system (AIS) data based ship-supply forecasting
Lechtenberg, Sandra; Siqueira Braga, Diego de; … - In: Digital transformation in maritime and city logistics : …, (pp. 3-24). 2019
experts, this work proposes a threestep process to forecast ship numbers. It implements, compares and evaluates different AI … method to forecast the number of ships in a certain region. It predicts the anchor time of each ship with an MAE of 5 days …
Persistent link: https://www.econbiz.de/10012158293
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IDR/USD forecasting : classical time series and artificial neural network method
Alam, M. F. Q.; Rikumahu, B. - In: Understanding digital industry : proceedings of the …, (pp. 227-231). 2020
Persistent link: https://www.econbiz.de/10012226403