In this paper a novel variant activation (transform) sigmoid function with three parameters is proposed, and then the improved BP algorithm based on it is educed and discussed, then Embedded Chaos-BP algorithm is proposed by means of combining the new fast BP algorithm and chaos optimization algorithm, Embedded chaos-BP algorithm converges fast and globally, and has no local minimum. The efficiency and advantage of our method is proved by simulation results of nonlinear function and prediction results of short-term load based on the improved and traditional BP ANNs. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Cheng, Q., & Liu, X. (2006). Short term load forecasting by using neural networks with variable activation functions and Embedded chaos algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3972 LNCS, pp. 1252–1258). Springer Verlag. https://doi.org/10.1007/11760023_182
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