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基于gλ变量的冗余优化模型
  • ISSN号：1001-7402
  • 期刊名称：《模糊系统与数学》
  • 时间：0
  • 分类：TP18[自动化与计算机技术—控制科学与工程;自动化与计算机技术—控制理论与控制工程]
  • 作者机构：[1]河北工程大学水电学院,河北邯郸056038, [2]河北工程大学数理科学与工程学院,河北邯郸056038
  • 相关基金：国家自然科学基金资助项目（61073121）;河北省应用基础研究计划重点基础研究项目（16964213D）;河北省教育厅青年基金项目（QN2015116）;邯郸市科学技术研究与发展计划项目（1528102058-5、1521109072-1）;河北省2016年研究生创新能力资助项目（222）
作者： 张鸿[1,2], 马丽涛[2], 哈明虎[1]
关键词： gλ变量, Sugeno测度空间, 冗余优化, Sugeno模拟, 混合智能算法, gλ Variable, Sugeno Measure Space, Redundancy Optimization, Sugeno Simulation, Hybrid Intelligent Algorithm
中文摘要：

为了解决Sugeno测度空间上系统寿命期望值、系统寿命的α乐观值和系统可靠性的系统性能优化问题，提出用gλ变量来表征冗余元件寿命的冗余优化模型。首先，建立Sugeno冗余期望值模型、Sugeno冗余机会约束规划模型和Sugeno冗余相关机会规划模型；其次，为了求解模型，设计一种基于Sugeno模拟、多层神经网络和遗传算法的混合智能算法；最后，通过桥式系统的系统性能优化的算例验证所提模型和算法的可行性。

英文摘要：

In order to solve the problems of system performance optimization for mean system-lifetime, α-system lifetime and system reliability on Sugeno measure space, redundancy optimization models which use gλ variable to characterize redundancy component life are provided. Firstly, Sugeno redundancy expected value model, Sugeno redundancy chance-constrained programming model and Sugeno redundancy dependent chance programming model are given. Then a hybrid intelligent approach which consists of Sugeno simulation,multilayer perceptron network and genetic algorithm is presented to solve the optimization. Finally, the feasibility of the optimization approach and hybrid approach is shown by the redundancy optimization for the system performance of bridge system.

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期刊信息
  • 《模糊系统与数学》
  • 中国科技核心期刊
  • 主管单位:国防科技大学
  • 主办单位:国防科技大学理学院 国防科技大学理学院
  • 主编：刘应明
  • 地址：湖南长沙国防科技大学理学院
  • 邮编：410073
  • 邮箱：fuzzysys@cfsm.cn
  • 电话：0731-84576220
  • 国际标准刊号：ISSN：1001-7402
  • 国内统一刊号：ISSN：43-1179/O1
  • 邮发代号:42-180
  • 获奖情况:
  • 美国《数学评论》（Mathematical Reviews）核心引...,中国科技论文统计源期刊,《中国科学引文数据库》来源期刊
  • 国内外数据库收录:
  • 美国数学评论（网络版）,德国数学文摘,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊（2004版）,中国北大核心期刊（2008版）,中国北大核心期刊（2011版）,中国北大核心期刊（2014版）
  • 被引量:8133