An approach to chance constrained problems using weighted empirical distribution and differential evolution with application to flood control planning

Author:

Tagawa Kiyoharu1,Miyanaga Shun2

Affiliation:

1. School of Science and Engineering Kindai University Higashi‐Osaka Japan

2. Graduate School of Science and Engineering Research Kindai University Higashi‐Osaka Japan

Funder

Grant-in-Aid for Scientific Research

Publisher

Wiley

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Networks and Communications,General Physics and Astronomy,Signal Processing

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Approximate Solution using Machine Learning and Evolutionary Algorithm for Large-Scale Data-Driven Chance Constrained Problems;2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS);2022-11-29

2. A Support Vector Machine-based Approach to Chance Constrained Problems using Huge Data Sets;Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications;2021-03-16

3. An Approach to Chance Constrained Problems Based on Huge Data Sets Using Weighted Stratified Sampling and Adaptive Differential Evolution;Computers;2020-04-16

4. Data Reduction via Stratified Sampling for Chance Constrained Optimization with Application to Flood Control Planning;Communications in Computer and Information Science;2019

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