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首页> 外文会议>International Symposium on Systems and Human Science; 20031119-20; Osaka(JP) >An Agent-Based Rules Discovery from Complex Database
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An Agent-Based Rules Discovery from Complex Database

机译：从复杂数据库发现基于代理的规则

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摘要

In this chapter, an agent-based approach to complex systems modeling is proposed. The requirement for complex systems modeling techniques is increasing in order to plan a safe, secure and reliable society, because more recently, most systems are becoming complex. This chapter describes agent-based clustering and an expression of the character of the obtained clusters. Each agent has a role to collect data points (objects) based on similarity, which is defined so that each agent can treat a mixed database. The interaction between the agents focuses on discussing the objects to consider all the attributes. The agent identifies an if-then rule based on the collected data and tries to determine variables for rule description. There is no objective function differing from the conventional mining methods, however, by taking this approach, there are some advantage points of the proposed method. One of the advantages is that it is not necessary to determine the number of the clusters before performing the process.
机译：在本章中，提出了一种基于代理的复杂系统建模方法。为了计划一个安全，有保障和可信赖的社会，对复杂系统建模技术的需求正在增加，因为最近，大多数系统都变得越来越复杂。本章介绍基于代理的聚类以及所获得聚类的特征表达。每个代理都具有根据相似性收集数据点（对象）的作用，该相似性已定义，以便每个代理可以处理混合数据库。代理之间的交互着重于讨论对象以考虑所有属性。代理根据收集的数据识别“如果-则-则”规则，并尝试确定用于规则描述的变量。没有目标函数与常规挖掘方法不同，但是，通过采用这种方法，该方法具有一些优点。优点之一是在执行该过程之前不必确定群集的数量。

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