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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

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

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

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

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

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

Purpose: The bulk cargo shipping industry is characterized by high cost pressure. Chartering vessels at low prices is important to increase the margin of transporting cargo. This paper proposes a three-step, AI-based methodology to support this by forecasting the number of available ships in a...

Persistent link: https://www.econbiz.de/10012158293

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

Out-of-sample stock return prediction using higher-order moments

Faias, José Afonso; Castel-Branco, Tiago - In: International journal of theoretical and applied finance 21 (2018) 6, pp. 1-27

Persistent link: https://www.econbiz.de/10011926608

Bayesian averaging of classical estimates in forecasting macroeconomic indicators with application of business survey data

Białowolski, Piotr; Kuszewski, Tomasz; Witkowski, Bartosz - In: Empirica : journal of european economics 41 (2014) 1, pp. 53-68

Persistent link: https://www.econbiz.de/10010437231

The value of robust statistical forecasts in the COVID-19 pandemic

Castle, Jennifer; Doornik, Jurgen A.; Hendry, David F. - In: National Institute economic review : journal of the … 256 (2021), pp. 19-43

Persistent link: https://www.econbiz.de/10012593668

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