D-S algorithm based on particle swarm optimizer

WANG Bo; WANG Chan-lin; LIANG Guo-qiang

doi:10.13873/j.1000-97872007.01.028

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D-S algorithm based on particle swarm optimizer

更新时间：2025-09-11

- D-S algorithm based on particle swarm optimizer
- Issue 1, Pages: 84-86(2007)
- 作者机构：
  
  1. 海军航空工程学院
  2. 海军航空工程学院,山东,烟台,264001
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872007.01.028
  CLC： TP301.6
- Published：2007
- 稿件说明：
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[1]王波,王灿林,梁国强.基于粒子群寻优的D-S算法[J].传感器与微系统,2007(01):84-86.

WANG Bo, WANG Chan-lin, LIANG Guo-qiang. D-S algorithm based on particle swarm optimizer[J]. 2007, (1): 84-86.
[1]王波,王灿林,梁国强.基于粒子群寻优的D-S算法[J].传感器与微系统,2007(01):84-86. DOI： 10.13873/j.1000-97872007.01.028.

WANG Bo, WANG Chan-lin, LIANG Guo-qiang. D-S algorithm based on particle swarm optimizer[J]. 2007, (1): 84-86. DOI： 10.13873/j.1000-97872007.01.028.

摘要

D-S证据理论是一种性能优越的信息融合方法

由于各传感器所提供的证据的重要程度不同

需要对各证据进行加权合成处理。目前的加权D-S证据理论限于合成规则的研究

较少讨论如何获取优化的证据权值。实际上

证据权值的确定是证据进行加权合成的基础和关键。针对加权证据理论的这一研究不足

提出了一种求取最佳证据权值的方法。首先

阐述了思想

再建立了优化模型;然后

改进了粒子群优化求解算法

利用其优越的求解非线性多峰值函数的能力

求解出了最优权值。通过实例仿真表明:这种证据理论的加权算法是有效的

与对比方法相比

具有更好的融合效果。

Abstract

The D-S evidence theory is an excellent method of information fusion.Because of the difference which is caused by the sensors

it is essential to deal with the evidence with a method of weighed D-S theory.Presently

the study of the weighed D-S theory is confined to synthetic methods

and the study on how to obtain better weight value is also rarely covered.In fact

the definition of the weight values is fundamental to the process of weight-synthesizing the evidence.Considering the disadvantages of the weighed D-S theory

a best method of obtaining evidence weight value is presented.After elaborating the thoughts of the new method

an excellent weight value is provided by establishing an optimized model and improving the particle swarm algorithm.Compared with the comparison methods

this evidence theory proves more effective by making simulation test.

关键词

Keywords

references

一种基于加权证据合成的多传感器目标识别方法 [J]. 刘海燕,赵宗贵,巴宏欣. 解放军理工大学学报(自然科学版) . 2005(06)

基于改进加权D-S信息融合的结构多损伤位置识别 [J]. 郭惠勇,张陵,周进雄. 工程力学 . 2005(01)

粒子群优化算法综述 [J]. 杨维,李歧强. 中国工程科学 . 2004(05)

Recent approaches to global optimization problems through Particle Swarm Optimization [J] . K.E. Parsopoulos,M.N. Vrahatis. Natural Computing . 2002 (2)

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