An intelligent system for forest fire risk prediction and fire fighting management in Galicia
| Autor: | José Luis Legido Soto, Elena Hernández-Pereira, Amparo Alonso-Betanzos, Oscar Fontenla-Romero, Bertha Guijarro-Berdiñas, Marı́a Inmaculada Paz Andrade, Eulogio Jiménez, Tarsy Carballas |
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| Přispěvatelé: | European Commission, Comisión Interministerial de Ciencia y Tecnología, CICYT (España) |
| Rok vydání: | 2003 |
| Předmět: |
Injury control
Neural Networks business.industry Accident prevention Forest fires Environmental resource management General Engineering Process improvement Poison control Firefighting Resources management Fire risk Computer Science Applications Common Risk category Fire risk prediction Artificial Intelligence Business intelligence Environmental science Knowledge intensive systems Kads business Simulation |
| Zdroj: | Digital.CSIC: Repositorio Institucional del CSIC Consejo Superior de Investigaciones Científicas (CSIC) Digital.CSIC. Repositorio Institucional del CSIC instname |
| DOI: | 10.13039/501100000780 |
| Popis: | Over the last two decades in southern Europe, more than 10 million hectares of forest have been damaged by fire. Due to the costs and complications of fire-fighting a number of technical developments in the field have been appeared in recent years. This paper describes a system developed for the region of Galicia in NW Spain, one of the regions of Europe most affected by fires. This system fulfills three main aims: it acts as a preventive tool by predicting forest fire risks, it backs up the forest fire monitoring and extinction phase, and it assists in planning the recuperation of the burned areas. The forest fire prediction model is based on a neural network whose output is classified into four symbolic risk categories, obtaining an accuracy of 0.789. The other two main tasks are carried out by a knowledge-based system developed following the CommonKADS methodology. Currently we are working on the trail of the system in a controlled real environment. This will provide results on real behaviour that can be used to fine-tune the system to the point where it is considered suitable for installation in a real application environment. This research has been funded by the European Regional Development Fund (ERDF) project 1FD97-1122-C06-01 and by the Spanish Comisión Interministerial de Ciencia y Tecnologı́a (CICYT) under project REN-2001-3216-CO4-01. |
| Databáze: | OpenAIRE |
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