Classification Learning System based on Multi-objective GA and Megathermal Weather Forecat

摘要：

A new classification learning system based on multiobjective GA is proposed in this paper. Firstly, the continuous attributes of samples are made discretion with a supervised segmentation method, so generalization and intelligibility of machine learning are improved. Moreover, comparison and selection mechanism based on partial order in set theory are infused into multi-objective GA. They enhance the ability to choose better chromosomes. The new algorithm is used to forecast megathermal weather in northern Zhejiang province. The experiment result indicates that it has unique intelligence, higher accuracy.

关键词： supervised segmentation method machine learning multi-objective GA megathermal weather forecast

作者: Zhang Hongwei Xu Jingxun Zou Shurong

作者单位: College of Computer Chengdu University of Information Technology Chengdu, P.R. China

会议类型: 国际会议

会议名称: 2011 2nd International Conference on Data Storage and Data Engineering(DSDE 2011)(2011年第二届数据存储与数据工程国际会议)

会议地点: 西安

会议语种:英文

页码: 203-206

在线出版日期: 2011-05-13（万方平台首次上网日期，不代表论文的发表时间）