摘要
针对公共危机应急系统数据库中数据庞杂,记录分类较难的情况,提出了一种采用遗传算法选择参数的模糊决策树算法,提高了决策树分类算法的准确率和得到规则的可解释性。将设计的分类器应用到实际的公安系统数据库当中,在对原有记录进行分类的基础上,得到了有效的规则,成功地帮助警务人员对当前的危急事件做出快速准确的预测和判断。
Nowadays the data in the real pohce database of the public critical system is explosive and hard to classify. To solve this problem, a revised fuzzy decision trees algorithm combined with the Genetic Algorithm was proposed in this paper. The forecast rate of the decision trees and the comprehensibility of the rules were improved by using this method. Meanwhile, the decision tree classifier based on the algorithm was designed to help the policemen not only to classify the old items, but also to forecast the new critical events accurately and quickly.
出处
《计算机应用》
CSCD
北大核心
2006年第10期2457-2459,共3页
journal of Computer Applications
基金
天津市科学技术委员会资助项目(043112911)
关键词
模糊决策树
参数选择
案件分类
遗传算法
fuzzy decision trees
parameter selection
case classification
Genetic Algorithm
