Data-Driven Modelling: Concepts, Approaches and Experiences

被引：0
|
作者：
Solomatine, D. [1 ]
See, L. M. [2 ]
Abrahart, R. J. [3 ]
机构：
[1] UNESCO IHE Inst Water Educ, POB 3015, NL-2601 DA Delft, Netherlands
[2] Univ Leeds, Sch Geog, Leeds LS2 9JT, W Yorkshire, England
[3] Univ Nottingham, Sch Geog, Nottingham NG7 2RD, England
来源：
PRACTICAL HYDROINFORMATICS: COMPUTATIONAL INTELLIGENCE AND TECHNOLOGICAL DEVELOPMENTS IN WATER APPLICATIONS | 2008年 / 68卷
关键词：
Data-driven modelling; data mining; computational intelligence; fuzzy rule-based systems; genetic algorithms; committee approaches; hydrology;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Data-driven modelling is the area of hydroinformatics undergoing fast development. This chapter reviews the main concepts and approaches of data-driven modelling, which is based on computational intelligence and machine-learning methods. A brief overview of the main methods - neural networks, fuzzy rule-based systems and genetic algorithms, and their combination via committee approaches is provided along with hydrological examples and references to the rest of the book.
引用
收藏
页码：17 / +
页数：5
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