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Evolutionary Optimisation Techniques to Estimate Input Parameters in Environmental Emergency Modelling

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Computational Optimization and Applications in Engineering and Industry

Part of the book series: Studies in Computational Intelligence ((SCI,volume 359))

Abstract

Parameter estimation in environmentalmodelling is essential for input parameters, which are difficult or impossible to measure. Especially in simulations for disaster propagation prediction, where hard real-time constraints have to be met to avoid tragedy, the additionally introduced computational burden of advanced global optimisation algorithms still hampers their use in many cases and poses an ongoing challenge. In this chapter we demonstrate how modifications of a Genetic Algorithm (GA) are able to decrease time-consuming fitness evaluations and hence to speed up parameter calibration. Knowledge from past observed catastrophe behaviour is used to guide the GA during various phases towards promising solution areas resulting in a fast convergence. Together with parallel computing techniques it becomes a viable estimation approach in environmental emergency modelling. Encouraging results were obtained in predicting forest fire spread.

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Author information

Authors and Affiliations

  1. Departament d’Arquitectura de Computadors i Sistemes Operatius, Escola d’Enginyeria, Universitat Autònoma de Barcelona, 08193, Bellaterra, Barcelona, Spain

    Kerstin Wendt, Ana Cortés & Tomàs Margalef

  2. Facultad de Ingeniería, Universidad Nacional de Río Negro, Sede Andina, San Carlos de Bariloche, Argentina

    Mónica Denham

Authors
  1. Kerstin Wendt
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  2. Mónica Denham
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  3. Ana Cortés
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  4. Tomàs Margalef
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Editors and Affiliations

  1. National Physical Laboratory, Mathematics and Scientific Computing, TW11 0LW, Teddington, Middlesex, UK

    Xin-She Yang

  2. Engineering Optimization & Modeling Center, School of Science and Engineering, Reykjavik University, Menntavegur 1, 101, Reykjavik, Iceland

    Slawomir Koziel

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Wendt, K., Denham, M., Cortés, A., Margalef, T. (2011). Evolutionary Optimisation Techniques to Estimate Input Parameters in Environmental Emergency Modelling. In: Yang, XS., Koziel, S. (eds) Computational Optimization and Applications in Engineering and Industry. Studies in Computational Intelligence, vol 359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20986-4_5

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  • DOI: https://doi.org/10.1007/978-3-642-20986-4_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20985-7

  • Online ISBN: 978-3-642-20986-4

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