Combining classification and regression trees and the neuro-fuzzy inference system for environmental data modeling

被引：4
|
作者：
Burrows, WR [1 ]
机构：
[1] Atmospher Environm Serv, Meteorol Res Branch, Downsview, ON M3H 5T4, Canada
来源：
18TH INTERNATIONAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS | 1999年
关键词：
D O I：
10.1109/NAFIPS.1999.781783
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A procedure is presented for dynamic-statistical modeling of predictands with non-linear predictand-predictor relationships when there are many potential predictors. Classification and Regression Trees (CART) is used for predictor selection and data stratification. CART output is suitable for piecewise-continuous predictands. Using predictors selected by CART, a neuro-fuzzy inference system (NFIS) algorithm produces an output model for continuous predictands. Application to modeling ground-level ozone is discussed.
引用
收藏
页码：695 / 699
页数：5
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