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。
Based on Bayesian approach, an optimal searching algorithm is proposed in the article to solve the problem of search- ing 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.
出处
《计算机与现代化》
2016年第10期21-24,29,共5页
Computer and Modernization
基金
国家级大学生创新训练项目(201610699315)
关键词
优化搜索算法
贝叶斯方法
概率分布
蒙特卡罗方法
optimal search algorithm
Bayesian approach
probability distribution
Monte-Carlo method
