Evolutionary intelligent system for input parameter optimisation in environmental modelling: A case study in forest fire forecasting

Kerstin Wendt*, Ana Cortés, Tomàs Margalef

*Corresponding author for this work

Research output: Chapter in BookChapterResearchpeer-review

1 Citation (Scopus)

Abstract

The need for input parameter optimisation in environmental modelling is a long-known and very time-consuming task. However, to avoid tragedy, disaster propagation predictions have to satisfy hard real-time constraints. Especially small disaster control centres with limited computing resources require fast and efficient calibration methods to deliver reliable predictions in time. The combination of a clustering method together with a Genetic Algorithm is used as parameter optimisation technique in forest fire spread prediction. We formalise and demonstrate the potential of the resulting Evolutionary Intelligent System's architecture to solve the complex problem of input parameter calibration on restricted simulation conditions.

Original languageAmerican English
Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
DOIs
Publication statusPublished - 2010

Publication series

Name2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

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