Short-term Wind Power Forecasting Based on BP Neural Network with Improved Ant Lion Optimizer
作者： Feng Jiang , Jiaqi He , Zijun Peng
DOI: 10.23919/CHICC.2018.8482950
关键词:
摘要: In order to improve the prediction accuracy of short-term wind power, this paper proposes a power model based on an improved ant lion optimizer algorithm optimize BP neural network (IALO-BP). The uses (IALO) weights and thresholds network, so as convergence rate generalization ability network. is tested by data Irish farm in November 2017. experimental results show that IALO can overcome defect original easy fall into local optimum speed slow. Moreover, IALO-BP superior GRNN SVR stability.
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