基于GA-BP神经网络的巨项目投入评价的改进研究

任宏, 马先睿, 刘华兵

系统工程理论与实践 ›› 2015, Vol. 35 ›› Issue (6) : 1474-1481.

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系统工程理论与实践 ›› 2015, Vol. 35 ›› Issue (6) : 1474-1481. DOI: 10.12011/1000-6788(2015)6-1474
论文

基于GA-BP神经网络的巨项目投入评价的改进研究

    任宏, 马先睿, 刘华兵
作者信息 +

Improvement of input evaluation for giant projects based on GA-BP neural network

    REN Hong, MA Xian-rui, LIU Hua-bing
Author information +
文章历史 +

摘要

考虑到巨项目巨大的资源投入量、投入产出的多样性、复杂性和社会性等特点, 根据决策"核心三原则"构建适宜的投入产出评价指标体系, 通过DEA法对巨项目各投入方案进行初评并筛选出有效的方案, 在此基础上运用遗传算法优化的BP神经网络(GA-BP), 结合DEA的初评结果对多个有效方案进行二次评价, 从而选择最优方案. 实证分析表明, 此改进的巨项目投入评价模型, 能较好地适应巨项目的特征, 既保证了投入评价的客观性, 又能够实现投入方案的完全排序.

Abstract

Considering a giant project's huge amount of resources input and diversity, complexity and social effect of its input and output, the input-output evaluation index system was established according to "three core principles". Each input scheme of the giant project was first evaluated by DEA method and effective input schemes were selected. Based on GA-BP neural network and results from first evaluation, multiple effective schemes were evaluated again to choose the optimal one. The empirical analysis shows that this improved evaluation model is adapt to characteristics of giant projects. It can not only guarantee the objectivity of giant projects input evaluation, but also achieve the goal to sequencing all input schemes.

关键词

巨项目 / 投入评价 / 决策三原则 / 遗传算法 / BP神经网络

Key words

giant project / input evaluation / three core principles / genetic algorithm / BP neural network

引用本文

导出引用
任宏 , 马先睿 , 刘华兵. 基于GA-BP神经网络的巨项目投入评价的改进研究. 系统工程理论与实践, 2015, 35(6): 1474-1481 https://doi.org/10.12011/1000-6788(2015)6-1474
REN Hong , MA Xian-rui , LIU Hua-bing. Improvement of input evaluation for giant projects based on GA-BP neural network. Systems Engineering - Theory & Practice, 2015, 35(6): 1474-1481 https://doi.org/10.12011/1000-6788(2015)6-1474
中图分类号: F282   

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基金

国家自然科学基金(51308567); 中央高校基本科研业务费科研专项(CDJSK12035503)
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