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Evaluating electric environmental issues using BP neural network with optimised hidden layer nodes

Author

Listed:
  • Dongxiao Niu
  • Jialiang Lv
  • Hongyan Liu

Abstract

BP neural network with optimum hidden layer nodes were used to evaluate the power environmental issues in China. Furthermore, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used to optimise the number of hidden layer nodes of BP neural network. The evaluation indices were determined through the training of the BP neural network with the samples. This new method is validated through a case study where power environmental issues were evaluated, and high accuracy rate and simple computation complexity were achieved. Therefore, the number of hidden layer nodes can be determined more scientifically and evaluation results derived by our method tend to be more accurate.

Suggested Citation

  • Dongxiao Niu & Jialiang Lv & Hongyan Liu, 2009. "Evaluating electric environmental issues using BP neural network with optimised hidden layer nodes," International Journal of Global Environmental Issues, Inderscience Enterprises Ltd, vol. 9(3), pages 227-238.
    • Handle: RePEc:ids:ijgenv:v:9:y:2009:i:3:p:227-238
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