An intelligent system for forest fire risk prediction and fire fighting management in Galicia

Expert Systems with Applications

Volumn 25, Issue 4, 2003, Pages 545-554

  Alonso Betanzos, Amparo ^a   Fontenla Romero, Oscar ^a   Guijarro Berdiñas, Bertha ^a   Hernández Pereira, Elena ^a   Paz Andrade, María Inmaculada ^b   Jiménez, Eulogio ^a   Soto, Jose Luis Legido ^c   Carballas, Tarsy ^d  

^a UNIVERSITY OF A CORUÑA   (Spain)

^b University of Santiago   (Spain)

^c UNIVERSITY OF VIGO   (Spain)

^d CSIC   (Spain)

Author keywords

CommonKads; Fire risk prediction; Forest fires; Knowledge intensive systems; Neural Networks; Resources management

Indexed keywords

DECISION MAKING; FIRE EXTINGUISHERS; FIRES; GEOGRAPHIC INFORMATION SYSTEMS; NEURAL NETWORKS; RESOURCE ALLOCATION; RISK MANAGEMENT;

FIRE FIGHTING;

EXPERT SYSTEMS;

EID: 0042510137     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0957-4174(03)00095-2     Document Type: Article

References (24)

1. Adlassnig K., Scheithauer W. Performance evaluation of medical expert systems using roc curves. Computers and Biomedical Research. 22:1989;297-313.
2. Alonso-Betanzos A., Fontenla-Romero O., Guijarro-Berdiñas B., Pereira E.H., Canda J., Jimenez E., Legido J., Muñiz S., Paz-Andrade C., Paz-Andrade M. A neural network approach for forestall fire risk estimation. Van Harmelen F. 15th European Conference on Artificial Intelligence (ECAI'02). 2002;643-647 IOS Press.
3. Avesani, P., Perini, A., & Ricci, F. (1993). Combining CBR and constraint reasoning in planning forest fire fighting. In: Proceedings of the First European Workshop on Case-Based Reasoning (pp. 235-239).
4. Bishop C. Neural networks for pattern recognition. 1995;Oxford University Press, New York.
5. Caballero D., Xanthopoulos G., Kallidromitou D., Lyrintzis G., Bonazountas M., Papachristou P., Pacios O. Fomfis: forest fire management and fire prevention system. Proceedings of the International Symposium on Forest Fires: Needs and Innovations. 1999;93-98.
6. CARICA (Cases Acquisition and Replay in Fire Campaign Ambience). URL http://sra.itc.it/projects/carica .
7. Chandler C., Cheney P., Thomas P., Trabaud L., Williams D. Fire in forestry. Vol. 1:1983.
8. Espinosa V., Galiñanes A., Paz-Andrade M., Legido J., Melikhova E. Testing weather-fire relationships in galicia (spain). III International Conference on Forest Fire Research. I:1998;1049-1060.
9. Gori M., Scarselli F. Are multiplayer perceptions adequate for pattern recognition and verification? IEEE Transactions on Pattern Analysis and Machine Intelligence. 20:(11):1998;1121-1131.
10. Hagan M., Menhaj M. Training feedforward networks with the marquardt algorithm. IEEE Transactions on Neural Networks. 5:(6):1994;989-993.
11. Haykin S. Neural networks. A comprehensive foundation. 1994;Macmillan, New York.
12. Hecht-Neilson R. Neurocomputing. 1990;Addison-Wesley, Reading, MA.
13. Kurková V. Kolmogorov's theorem in relevant. Neural Computation. 2:(4):1991;617-622.
14. Merida, J. (2002). Estrategia de la administración del estado en la defensa contra incendios forestales, Technical report, Dirección General de Conservación de la Naturaleza, Ministerio de Medio Ambiente de Espana.
15. PIROMACOS, (2002). Sistema para la Prevención y Control de Incendios Forestales. URL http://www.infonegocio.com/ici/piromacos.htm .
16. Paz López, (2002). Un sistema inteligente para la gestión eficiente de recursos en la lucha contra incendios forestales, Master's thesis, Department of Computer Science. University of A Coruña.
17. Reifsnyder, W. & Albers, B. (1994). Systems for evaluation and predicting the effects of weather and climate on wideland fires. World Meteorological Organizations 496.
18. Ricci, F., Mam, S., Marti, P., Normand, V., & Olmo, P. (1994). Charade: a platform for emergencies management systems. Technical Report 9404-07, IRST.
19. Riley, G. (2002). Clips web page. URL http://www.ghg.net/clips/CLIPS.html.
20. San-Miguel-Ayanz, J., Barbosa, P., Schmuck, G., Schulte, E., & Barisisch, A. (2001). European forest fire risk assessment and burnt area mapping. Proceedings of the International Conference Forest Fires.
21. Schreiber A., Akkermans J., Anjewierden A., De Hoog R., Shadbolt N., Van de Velde W., Wielinga B. Knowledge engineering and management. The CommonKADS methodology. 2000;MIT Press.
22. Sebastian Lopez, A., Salvador, R., & San-Miguel-Ayanz, J. (2001). Two models for a structural forest fire risk index at a regional scale. Proceedings of the 21st EARSeL Workshop Remote Sensing and GIS Applications to Forest Fire Management.
23. U.F. Service, (2002). Fire management tools online. URL http://fire.org/perl/tools.cgi .
24. Weiss S., Kulikowski C. Computer systems that learn: Classification and prediction methods from statistics, neural nets, machine learning and expert systems. 1990;Morgan Kaufmann, San Mateo, CA.