College of Water Conservancy and Hydropower, Hohai University, Nanjing, China

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Abstract—Aiming at the problems such as peoples’ influence, the poor objectivity and comparability of traditional evaluation methods, a chaotic neural network comprehensive evaluation model is established, coupled the ergodicity characteristic of chaotic motion with the neural network. In the model, chaotic learning algorithm is constructed, the sequences are generated by chaotic maps to guide the search process to achieve optimization problem in limited range, the neural network algorithm is adopted to achieve fast optimization extreme in the range of each local interval, and the elitist strategy is used to make the algorithm converge to the global optimization. An example of the effect evaluation of water resources allocation is studied with the model, which shows that the model is simpler in principle, more convenient in calculation, more accurate for results, and it has strong adaptability and replicability.

Index Terms—chaotic neural network, comprehensive evaluation model, water resources allocation, effect evaluation, index system, entropy

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Cite: Xianfeng Huang and Guohua Fang, " Water Resources Allocation Effect Evaluation Based on Chaotic Neural Network Model," Journal of Computers vol. 5, no. 8, pp. 1169-1176, 2010.