基于贝叶斯方法的失踪目标优化搜索算法

doi:10.3969/j.issn.1006-2475.2016.10.005

计算机与现代化

基于贝叶斯方法的失踪目标优化搜索算法

1.西北工业大学理学院，陕西西安710072；2.西北工业大学航天学院，陕西西安710072

收稿日期:2016-03-24 出版日期:2016-10-15 发布日期:2016-10-14
作者简介:于美（1983-），女，辽宁大连人，西北工业大学理学院讲师，博士，研究方向：偏微分方程理论及其应用；徐子健（1996-），男，河南商丘人，西北工业大学航天学院本科生，研究方向：飞行器设计与工程。
基金资助:
基金项目：国家级大学生创新训练项目（201610699315）

Optimal Search Algorithm for Missing Target Based on Bayesian Approach

1. School of Natural and Applied Sciences, Northwestern Polytechnical University, Xi’an 710072, China;

2. School of Astronautics, Northwestern Polytechnical University, Xi’an 710072, China

Received:2016-03-24 Online:2016-10-15 Published:2016-10-14

摘要/Abstract

摘要：
摘要：针对特定区域失踪目标的搜索问题，提出一种基于贝叶斯方法的失踪目标优化搜索算法。首先介绍贝叶斯方法的应用以及搜索算法的优化，然后利用蒙特卡罗方法对不同的搜索算法进行模拟与比较，模拟结果显示基于贝叶斯方法的搜索算法与随机搜索、线性搜索相比具有明显的优势。同时还进一步探究了不同的区域网格数量对结果的影响。

关键词: 优化搜索算法, 贝叶斯方法, 概率分布, 蒙特卡罗方法

Abstract: Based on Bayesian approach, an optimal searching algorithm is proposed in the article to solve the problem of searching for missing target in a particular area. This article introduces the application of Bayesian approach and optimization method of searching strategy, then simulating the searching process of different strategies and making comparisons. The results indicate that this strategy put forward in this article is more effective than random search and linear search. This article also explores the effects of the quantity of grids on search efficiency.

Key words: optimal search algorithm, Bayesian approach, probability distribution, MonteCarlo method

中图分类号:

TP301.6

于美1，徐子健2. 基于贝叶斯方法的失踪目标优化搜索算法[J]. 计算机与现代化, doi: 10.3969/j.issn.1006-2475.2016.10.005.

YU Mei1, XU Zijian2. Optimal Search Algorithm for Missing Target Based on Bayesian Approach[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2016.10.005.

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基于贝叶斯方法的失踪目标优化搜索算法

Optimal Search Algorithm for Missing Target Based on Bayesian Approach

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