野草猴群算法的传感器优化布置方法研究

计算机工程与科学

野草猴群算法的传感器优化布置方法研究

殷红1，杜国璋1，彭珍瑞1，马丽2

（1.兰州交通大学机电工程学院，甘肃兰州 730070；

2.兰州交通大学自动化与电气工程学院，甘肃兰州 730070）

收稿日期:2016-05-16 修回日期:2016-09-30 出版日期:2018-04-25 发布日期:2018-04-25
基金资助:
国家自然科学基金（61463028）；甘肃省自然科学基金（17JR5RA102）

A weed monkey algorithm for optimal sensor placement

YIN Hong1,DU Guozhang1,PENG Zhenrui1,MA Li2

（1.School of Mechatronic Engineering,Lanzhou Jiaotong University,Lanzhou 730070;

2.School of Automation and Electrical Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China）

Received:2016-05-16 Revised:2016-09-30 Online:2018-04-25 Published:2018-04-25

摘要/Abstract

摘要：

简易猴群算法存在初始化分布随机、爬步长固定、优秀猴子特征信息不能传承等缺陷，使算法求解性能受限。为解决以上问题，提出了一种用于传感器优化布置的野草猴群算法。该算法利用正态分布方法提高初始种群的多样性；采取自适应爬步长提升求解速度和搜索精度；融入野草繁殖进化和竞争排斥机制，扩大后代种群繁殖中优秀猴子的影响范围。以常用的模态置信度矩阵为传感器优化布置的目标函数，配置传感器的布置位置。以常用的8个测试函数和3个常用算法对其进行分析，验证了算法的可行性和有效性。最后以糊底机涂胶机构为例，进行传感器优化布置方案选择。实验结果表明，野草猴群算法的求解精度较简易猴群算法有大幅提高。

关键词: 传感器优化布置, 野草猴群算法, 正态分布, 爬步长, 繁殖进化, 竞争生存

Abstract:

The simple monkey algorithm has the shortcomings of initial distribution randomization, fixed climb step length and incapability of inheriting the characteristics of excellent monkeys, which limits the solution performance of the algorithm. In order to solve the above problems, a weed monkey algorithm for optimal sensor placement is proposed. Normal distribution is used to enhance the diversity of initial monkey populations. Selfadaptive climb step is introduced to improve the solution accuracy and convergence rate. Both weed reproduction evolution and competitive exclusion mechanism are used to enlarge the influence of excellent monkey on the monkey offspring population. The commonly used Modal Assurance Criterion (MAC) is used as the objective function of optimal sensor placement. The commonly used 8 test functions and 3 algorithms are used to verify the feasibility and effectiveness of the algorithm. Finally, the optimal sensor placement is carried out on the gelatinize mechanism of bag bottompasting machine. The results show that, compared with the simple monkey algorithm, the solution accuracy of the weed monkey algorithm precision is greatly improved.

Key words: optimal sensor placement, weed monkey algorithm, normal distribution, climbing step, reproduction evolutionary, competitive survival

殷红1，杜国璋1，彭珍瑞1，马丽2. 野草猴群算法的传感器优化布置方法研究[J]. 计算机工程与科学.

YIN Hong1,DU Guozhang1,PENG Zhenrui1,MA Li2.

A weed monkey algorithm for optimal sensor placement

[J]. Computer Engineering & Science.

[1]	李康顺，王法杰，张楚湖，杨磊，陈琰. 一种基于JADE改进的差分演化算法[J]. J4, 2015, 37(09): 1698-1706.
[2]	杨鹤标，刘玲，杨立凡. 基于结构相似匹配的SQL程序自动评估模型研究[J]. J4, 2010, 32(11): 92-96.