Inverse research for gravity dam parameters based on chaos artificial fish swarm algorithm

SONG Zhi-yu; LI Jun-jie; WANG Hong-yu

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Inverse research for gravity dam parameters based on chaos artificial fish swarm algorithm

更新时间：2026-06-25

- Inverse research for gravity dam parameters based on chaos artificial fish swarm algorithm
- Vol. 28, Issue 10, (2007)
- 作者机构：
  
  1. 黄河勘测规划设计有限公司,郑州,450003
  2. 大连理工大学土木水利学院,大连,116023
  3. 中国长江三峡工程开发总公司,宜昌,443002
- 作者简介：
- 基金信息：
- DOI：
  CLC： TB115
- Online First：15 October 2013，
  
  Published：2007
- 稿件说明：
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SONG Zhi-yu, LI Jun-jie, WANG Hong-yu. Inverse research for gravity dam parameters based on chaos artificial fish swarm algorithm[J]. 2007, 28(10).
DOI：

SONG Zhi-yu, LI Jun-jie, WANG Hong-yu. Inverse research for gravity dam parameters based on chaos artificial fish swarm algorithm[J]. 2007, 28(10). DOI：

摘要

首先介绍了一种随机搜索优化方法—人工鱼群算法（AFSA），同时根据混沌（CHAOS）的遍历性和随机性等特点，将混沌系统和人工鱼群算法相结合形成了一种新的融合优化算法—混沌人工鱼群算法（CAFSA）。将混沌人工鱼群算法应用到混凝土大坝材料参数反演中。经算例分析表明，与人工鱼群算法相比较，混沌人工鱼群算法具有收敛快、效率高和结果精度高等优点。从而为解决类似的系统优化和参数识别问题提供了一种新的方法。

Abstract

A new stochastic search optimization algorithm

artificial fish swarm algorithm (AFSA )

is presented firstly; and according to the ergodicity and stochasticity of chaos

we combined artificial fish swarm algorithm and chaos to form a new fusion optimization algorithm

chaos artificial fish swarm algorithm(CAFSA). Then CAFSA is applied to inverse the parameters of gravity dam. Results of computation example show that CAFSA has the advantages of rapid convergence rate

high optimization efficiency and high inversion accuracy; so a new way for solving the problem of optimization and identification is provided.

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