Abstract—The evolution stage classification which contains adolescence, adulthood, and old age of China rift lakes was constructed by using BP neural network model. In this paper, the model was applied to eleven lakes from Yunnan Plateau Lakes region and the middle and lower reaches of the Yangtze River plain. Through the selection of training samples, test samples and optimal number of hidden layer nodes to determine, the precision of BP neural network classification is supposed suitable for evolution stage classification of rift lakes. According to the classification results, dianchi lake is an old age lake, erhai lake, chenghai lake, xingyun lake, yilong lake, qilu lake, yangzong lake and chaohu lake are all in adulthood, and fuxian lake, lugu lake and poyang lake are in adolescence.
Index Terms—Evolution stage classification, rift lakes, BP neural network.
T. Zhang and W. H. Zeng are with State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China (e-mail: zhangting08@ieecas.cn; zengwh@bnu.edu.cn).
F. L. Yang is with Yunnan Institute of Environmental Science, Kunming, China (e-mail: yfl@yies.org.cn).
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Cite: T. Zhang, W. H. Zeng, and F. L. Yang, "Applying a BP Neural Network Approach to the Evolution Stage Classification of China Rift Lakes," International Journal of Modeling and Optimization vol. 4, no. 6, pp. 450-454, 2014.
