Application of adaptive fuzzy rule-based models for reconstruction of missing precipitation events

被引：62

作者：

Abebe, AJ ^{[1
]}

Solomatine, DP ^{[1
]}

Venneker, RGW ^{[1
]}

机构：

[1] IHE Delft, Int Inst Infrastructural Hydraul & Environm Engn, NL-2601 DA Delft, Netherlands

来源：

HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES | 2000年 / 45卷 / 03期

关键词：

D O I：

10.1080/02626660009492339

中图分类号：

TV21 [水资源调查与水利规划];

学科分类号：

081501 ;

摘要：

This paper describes a fuzzy rule-based approach applied for reconstruction of missing precipitation events. The working rules are formulated from a set of past observations using an adaptive algorithm. A case study is carried out using the data from three precipitation stations in northern Italy. The study evaluates the performance of this approach compared with an artificial neural network and a traditional statistical approach. The results indicate that, within the parameter sub-space where its rules are trained, the fuzzy rule-based model provided solutions with low mean square error between observations and predictions. The problems that have yet to be addressed are overfitting and applicability outside the range of training data.

引用

页码：425 / 436

页数：12