Forecasting Research on the Profitability of China's New Energy Generation Based on MLP and RBF Neural Network

Yuan Wang, Suli Yan

Abstract


This paper mainly forecasts the new energy and power’s profitability of Zhejiang province in China from 2015 to 2021. Firstly, data of new energy and power’s profitability and its influencing factors are collected and processed. Secondly, the neural network models (MLP and RBF neural network) are selected for the profitability forecasting and SPSS software is used for modeling. Finally, this paper analyses the forecasting values of each models and predicts the income of new energy generation in Zhejiang province in the next 6 years and selects the best prediction results as a reference.

Keywords


New Energy Generation, Profitability Forecasting, Artificial Neural Network

Publication Date


2016-11-18 00:00:00


DOI
10.12783/dteees/peee2016/3781

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