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  • Search: subject:"Combination forecasting"
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Year of publication
Subject
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Forecasting model 4 Prognoseverfahren 4 ARIMA transfer function 2 Artificial Neural Network (ANN) 2 Combination Forecasting 2 Constrained weighted least squares (WLS) regression analysis 2 Gradient Algorithm constrained optimization 2 Nichtparametrisches Verfahren 2 Nonparametric statistics 2 Simulation Methods 2 Structural Break Model 2 Structural break 2 Strukturbruch 2 Theorie 2 Theory 2 Time series analysis 2 Zeitreihenanalyse 2 combination forecasting 2 steel price forecasts 2 Algorithm 1 Algorithmus 1 Artificial intelligence 1 Automotive industry 1 Combination forecasting 1 Demand 1 Estimation 1 Estimation theory 1 Forecast 1 Harmony Search algorithm 1 Intelligent supply chain management 1 Intermittent demand 1 Kfz-Industrie 1 Künstliche Intelligenz 1 Lieferkette 1 Local Linear Fitting 1 Machine learning 1 Mathematical programming 1 Mathematische Optimierung 1 Model Averaging 1 Multifold Cross-Validation 1
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Online availability
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Free 6 CC license 2
Type of publication
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Article 4 Book / Working Paper 2
Type of publication (narrower categories)
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Arbeitspapier 2 Article in journal 2 Aufsatz in Zeitschrift 2 Graue Literatur 2 Non-commercial literature 2 Working Paper 2 Article 1
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Language
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English 5 Undetermined 1
Author
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Cai, Zongwu 2 Gunawan 2 Terregrossa, Salvatore Joseph 2 Şener, Uğur 2 Chang, Hong 1 Chen, Aihui 1 Sun, Wei 1 Sun, Yuying 1 Wang, Jingmin 1 Yu, Ying 1 Zhuang, Xiaotian 1
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Published in...
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Working papers series in theoretical and applied economics 2 Cogent Economics & Finance 1 Cogent economics & finance 1 Data science and management : DSM 1 Energies 1
Source
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ECONIS (ZBW) 4 EconStor 1 RePEc 1
Showing 1 - 6 of 6
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A new nonparametric combination forecasting with structural breaks
Cai, Zongwu; Gunawan; Sun, Yuying - 2024
Persistent link: https://www.econbiz.de/10015076828
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Employing a generalized reduced gradient algorithm method to form combinations of steel price forecasts generated separately by ARIMA-TF and ANN models
Terregrossa, Salvatore Joseph; Şener, Uğur - In: Cogent Economics & Finance 11 (2023) 1, pp. 1-25
The research objective of the present study is the development of a model for increased accuracy of steel-price forecasts, which is of paramount importance for firms who use steel as an input and thus need to make informed decisions with regard to an optimal amount and type of hedge against...
Persistent link: https://www.econbiz.de/10015074896
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A combination forecast for nonparametric models with structural breaks
Cai, Zongwu; Gunawan - 2023
Persistent link: https://www.econbiz.de/10014414260
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Employing a generalized reduced gradient algorithm method to form combinations of steel price forecasts generated separately by ARIMA-TF and ANN models
Terregrossa, Salvatore Joseph; Şener, Uğur - In: Cogent economics & finance 11 (2023) 1, pp. 1-25
The research objective of the present study is the development of a model for increased accuracy of steel-price forecasts, which is of paramount importance for firms who use steel as an input and thus need to make informed decisions with regard to an optimal amount and type of hedge against...
Persistent link: https://www.econbiz.de/10014500535
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A combined forecasting method for intermittent demand using the automotive aftermarket data
Zhuang, Xiaotian; Yu, Ying; Chen, Aihui - In: Data science and management : DSM 5 (2022) 2, pp. 43-56
demand combination forecasting method based on internal and external data, builds intermittent demand feature engineering … data of the enterprise, and proposes two combination forecasting optimization methods on the basis of the best …
Persistent link: https://www.econbiz.de/10014517937
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Forecasting Annual Power Generation Using a Harmony Search Algorithm-Based Joint Parameters Optimization Combination Model
Sun, Wei; Wang, Jingmin; Chang, Hong - In: Energies 5 (2012) 10, pp. 3948-3971
Accurate power generation forecasting provides the basis of decision making for electric power industry development plans, energy conservation and environmental protection. Since the power generation time series are rarely purely linear or nonlinear, no single forecasting model can identify the...
Persistent link: https://www.econbiz.de/10010676093
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