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松花江流域蓄滞洪区方案优选智能决策研究
引用本文:陈守煜,于义彬,马用祥.松花江流域蓄滞洪区方案优选智能决策研究[J].大连理工大学学报,2003,43(3):362-366.
作者姓名:陈守煜  于义彬  马用祥
作者单位:1. 大连理工大学,土木水利学院,辽宁,大连,116024
2. 东北勘测设计院,规划室,吉林,长春,130021
摘    要:针对松花江流域防洪工程重要组成部分的蓄滞洪区,基于陈守煜提出的模糊优选BP神经网络模型,引入了遗传算法,提出融入遗传算法的模糊优选神经网络智能决策模型,对松花江流域蓄滞洪区方案优选进行智能决策.该模型既能合理地构造神经网络的拓扑结构,又可加快网络的收敛速度,并能改善网络的全局寻优能力,是对模糊优选BP神经网络模型的进一步发展,同时更对松花江流域蓄滞洪区的优选提供了理论依据.

关 键 词:松花江流域  防洪工程  蓄滞洪区  方案优选  智能决策  遗传算法  模糊优选BP神经网络模型
文章编号:1000-8608(2003)03-0362-05

Intelligent decision on optimization of storage-detention flood area alternatives in Songhua River basin
Abstract:In order to solve the optimization problem of the storage\|detention flood area alternatives of Songhua River basin, this paper imported GAs based on the fuzzy optimization BP neural network which was proposed by Chen Shouyu, established a neural network model of fuzzy optimization mixing with Genetic Algorithms, and made an intelligent decision for alternatives optimization of storage\|detention flood area in Songhua River basin, which can not only build reasonable network structure, but increase the convergence speed. More feasible and more persuasive conclusion can be drawn, and at the same time, the intelligent decision model can further develop the BP neural network model of fuzzy optimization, which has theoretic and applicable value.
Keywords:decision-making  optimization  neural network  genetic algorithm  fuzzy
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