A multi-model approach to analysis of environmental phenomena

被引：103

作者：

Giustolisi, O.

Doglioni, A.

Savic, D. A.

Webb, B. W.

机构：

[1] Tech Univ Bari, Engn Fac Taranto, Dept Civil & Environm Engn, I-74100 Taranto, Italy

[2] Univ Exeter, Ctr Water Syst, Dept Engn, Sch Engn Comp Sci & Math, Exeter EX4 4QX, Devon, England

[3] Univ Exeter, Dept Geog, Sch Geog Archaeol & Earth Resources, Exeter EX4 4RJ, Devon, England

来源：

ENVIRONMENTAL MODELLING & SOFTWARE | 2007年 / 22卷 / 05期

关键词：

scientific knowledge discovery from data; environmental modelling; evolutionary computing; Evolutionary Polynomial Regression; data reconstruction;

D O I：

10.1016/j.envsoft.2005.12.026

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A data-driven methodology named Evolutionary Polynomial Regression is introduced. EPR permits the symbolic and multi-purpose modelling of physical phenomena, through the simultaneous solution of a number of models. Multi-purpose modelling or "multi-modelling" enables the user to make a different choice according to what the model is aiming at: (a) the scientific knowledge based on data modelling, (b) on-line and off-line forecasting, (c) data augmentation (i.e. infilling of missing data in time series) and so on. This allows a more robust model selection phase. A case study based on the application of Evolutionary Polynomial Regression to the study of the thermal behaviour of a stream is presented. (c) 2006 Elsevier Ltd. All rights reserved.

引用

页码：674 / 682

页数：9

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