摘要
自然灾害已严重威胁人们的生命财产安全,影响天气变化的因素多而复杂,致使灾害天气的准确预测预报相当困难.本文从局部区域出发,应用多组合器协同分析方法,探讨局域环境下的气象数据挖掘问题,提出了一个多组合器协同分析模型,实现了各基分类器和组合器的建模,通过对气象数据的实证性分析与实验,验证了本模型有较高的分类准确率和快速分类能力.
Natural disasters injure people and damage property .Because the weather is related to many factors, it is difficult to forecast accurately the disastrous weather .Based on multi-classifiers, a coopera-tive data mining method is proposed .A cooperative classification model is designed and implemented , which is composed of base classifiers and an integration classifier .The model is used to mine local area meteorological data .Experimental results show that the model has high classification accuracy and effi-cient ability .
出处
《广东工业大学学报》
CAS
2014年第1期25-31,共7页
Journal of Guangdong University of Technology
基金
教育部重点实验室基金资助项目(110411)
广东省自然科学基金资助项目(10451009001004804
9151009001000007)
广东省科技计划项目(2012B091000173)
广州市科技计划项目(2012J5100054
2013J4500028)
韶关市科技计划资助项目(2010CXY/C05)
关键词
数据挖掘
K-最近邻算法
协同
组合分析器
局域气象数据
data mining
K-Nearest Neighbor algorithm
cooperative
multi-classifier model
local area meteorological data
