Study on Economic Data Forecasting Based on Hybrid Intelligent Model of Artificial Neural Network Optimized by Harris Hawks Optimization
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- Naiming Xie & Alan Pearman, 2014. "Forecasting energy consumption in China following instigation of an energy-saving policy," 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. 74(2), pages 639-659, November.
- Longo, Luigi & Riccaboni, Massimo & Rungi, Armando, 2022.
"A neural network ensemble approach for GDP forecasting,"
Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
- Luigi Longo & Massimo Riccaboni & Armando Rungi, 2021. "A Neural Network Ensemble Approach for GDP Forecasting," Working Papers 02/2021, IMT School for Advanced Studies Lucca, revised Mar 2021.
- Lamichhane, Sabhyata & Mei, Bin & Siry, Jacek, 2023. "Forecasting pine sawtimber stumpage prices: A comparison between a time series hybrid model and an artificial neural network," Forest Policy and Economics, Elsevier, vol. 154(C).
- Eklund, Jana & Kapetanios, George, 2008.
"A review of forecasting techniques for large datasets,"
National Institute Economic Review, Cambridge University Press, vol. 203, pages 109-115, January.
- Jana Eklund & George Kapetanios, 2008. "A Review of Forecasting Techniques for Large Data Sets," Working Papers 625, Queen Mary University of London, School of Economics and Finance.
- Jana Eklund & George Kapetanios, 2008. "A Review of Forecasting Techniques for Large Data Sets," Working Papers 625, Queen Mary University of London, School of Economics and Finance.
- Christos Avdoulas & Stelios Bekiros & Sabri Boubaker, 2018. "Evolutionary-based return forecasting with nonlinear STAR models: evidence from the Eurozone peripheral stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 307-333, March.
- Eklund, Jana & Kapetanios, George, 2008.
"A review of forecasting techniques for large datasets,"
National Institute Economic Review, National Institute of Economic and Social Research, vol. 203, pages 109-115, January.
- Jana Eklund & George Kapetanios, 2008. "A review of forecasting techniques for large datasets," National Institute Economic Review, National Institute of Economic and Social Research, vol. 203(1), pages 109-115, January.
- Jana Eklund & George Kapetanios, 2008. "A Review of Forecasting Techniques for Large Data Sets," Working Papers 625, Queen Mary University of London, School of Economics and Finance.
- Flores, Juan J. & Graff, Mario & Rodriguez, Hector, 2012. "Evolutive design of ARMA and ANN models for time series forecasting," Renewable Energy, Elsevier, vol. 44(C), pages 225-230.
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Keywords
economic data forecasting; basic model; ANN model; hybrid intelligent model; HHO;All these keywords.
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