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论文:2016,Vol:34,Issue(4):691-697 |
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引用本文： |
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李哲, 慕德俊, 张天凡, 黄一杰. 基于agent形态特征的聚类分析研究与应用[J]. 西北工业大学学报 |
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Li Zhe, Mu Dejun, Zhang Tianfan, Huang Yijie. Clustering Algorithm and its Application Base on Agent Morphology[J]. Northwestern polytechnical university |
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| 基于agent形态特征的聚类分析研究与应用 |
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| 李哲, 慕德俊, 张天凡, 黄一杰 |
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| 西北工业大学 自动化学院, 陕西 西安 710072 |
| 摘要: |
| 目前在多智能体（agent）系统控制中，少量agent在行为上表现出较强的独立性，但在宏观上依然具有一定的相似性，当其规模较大时这种相似性会更加明显，但随着数量增加的同时控制系统的负担也会快速增长并导致决策延迟或无效化。提出一种基于形态特征的聚类算法，尝试将具有相似行为的agent进行聚类研究，以较少的聚类中心替代数量庞大的agent以简化分析控制流程以提高效率。通过与K-means聚类算法的对比测试与分析，该算法能够有效简化系统复杂性，提升系统性能，并具有较强的稳定性。 |
| 关键词:
图像形态学
聚类分析
机器视觉
机器学习
K-means算法
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| Clustering Algorithm and its Application Base on Agent Morphology |
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| Li Zhe, Mu Dejun, Zhang Tianfan, Huang Yijie |
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| School of Automation, Northwestern PolytechnicalUniversity, Xi'an 710072, China |
| Abstract: |
| In multi-agent control system, a small amount of Agent showed a greater independence in behavior, but still has some similarity in macro, especially in a situation with more number of Agent is most evident in when the agent number will make the burden of control system of fast-growing and eventually led to the decision to postpone or invalidation. Clustering algorithm based on morphological characteristics of agent is proposed, try clustering research agent with similar behavior, cluster Centre substitute with less amount of agent in order to simplify the analysis of control processes to improve efficiency. Through comparison with K-means clustering algorithm testing and analysis, the algorithm can simplify the complexity; improve system performance, and better stability. |
| Key words:
cluster analysis
mage morphology
cluster algorithm
matlab
real time control
machine vision
machine learning
K-means algorithm
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| 收稿日期: 2015-10-12
修回日期:
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| DOI: |
| 基金项目: 湖北省自然科学基金（2014CFB576）、湖北工程学院自然科研项目（z2013016、z201515）及湖北工程学院新技术学院自然科研项目（Hgxky14）资助 |
| 通讯作者:
Email： |
| 作者简介: 李哲(1986-),西北工业大学博士研究生,主要从事网络信息安全、智能体协同控制的研究。
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