Abstract
This paper presents a combination of GRNN neural network and fuzzy neural network prediction model, based on the energy-related data from 1997 to 2016 to establish a model, and use it for practical applications. The actual forecast predicts that the combined forecast model in the actual forecast Effectiveness. And predict energy demand in the next three years. The results show that the combined forecasting model is superior to the single forecasting model in general, and the combined forecasting model has high forecasting accuracy and strong practicality.
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Acknowledgements
This work is supported by Ministry of Education Humanities and Social Science Planning Fund Project (16YJA630002), Heilongjiang Social Science Fund Project (15GLB05) and Fundamental Research Funds for Central Universities (HEUCF180911). This paper is funded by the International Exchange Program of Harbin Engineering University for Innovation-oriented Talents Cultivation.
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Cao, J., Zhou, X. (2020). China’s Energy Demand Forecast Based on Combination Model. In: Li, X., Xu, X. (eds) Proceedings of the Sixth International Forum on Decision Sciences. Uncertainty and Operations Research. Springer, Singapore. https://doi.org/10.1007/978-981-13-8229-1_12
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DOI: https://doi.org/10.1007/978-981-13-8229-1_12
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