• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Uncertainty Analysis and Applications >Dependent-Chance Programming on Sugeno Measure Space
【24h】

Dependent-Chance Programming on Sugeno Measure Space

机译：Sugeno度量空间的相依机会编程

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In order to solve the optimization problem of selecting the decision with maximal chance to meet the Sugeno event in Sugeno environment, dependent-chance programming on Sugeno measure space is proposed, which can be considered as a generalized extension of the stochastic dependent-chance programming. Firstly, the theoretical framework of dependent-chance programming on Sugeno measure space is established. Secondly, a Sugeno simulation-based hybrid approach, which consists of back propagation neural network and genetic algorithm, is presented to construct an approximate solution of the complex dependent-chance programming models on Sugeno measure space. Finally, some numerical examples are given to illustrate the effectiveness of the approach.
机译：为了解决在Sugeno环境中选择具有最大机会满足Sugeno事件的决策的优化问题，提出了Sugeno度量空间上的依赖机会编程，可以将其视为随机依赖机会编程的广义扩展。首先，建立了Sugeno度量空间上依赖机会编程的理论框架。其次，提出了一种基于Sugeno仿真的混合方法，该方法包括反向传播神经网络和遗传算法，以构造Sugeno测度空间上复杂依赖机会编程模型的近似解。最后，通过数值例子说明了该方法的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号