A data fusion framework with novel hybrid algorithm for multi-agent Decision Support System for Forest Fire

ELMAS Ç., SÖNMEZ Y.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.38, sa.8, ss.9225-9236, 2011 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 38 Sayı: 8
  • Basım Tarihi: 2011
  • Doi Numarası: 10.1016/j.eswa.2011.01.125
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.9225-9236
  • Anahtar Kelimeler: Detection and prediction of forest fire, Artificial Neural Network, Naive Bayes Classifier, Fuzzy Switching, Decision Support System, INTELLIGENT SYSTEM, NEURAL-NETWORKS
  • Gazi Üniversitesi Adresli: Evet

Özet

In this study Forest Fire Decision Support System (FOFDESS) which is a multi-agent Decision Support System for Forest Fire has been presented. Depending on the existing meteorological state and environmental observations, FOFDESS does the fire danger rating by predicting the forest fire and it can also approximate fire spread speed and quickly detect a started fire. Some data fusion algorithms such as Artificial Neural Network (ANN), Naive Bayes Classifier (NBC), Fuzzy Switching (FS) and image processing have been used for these operations in FOFDESS. These algorithms have been brought together by a designed data fusion framework and a novel hybrid algorithm called NABNEF (Naive Bayes Aided Neural-Fuzzy Algorithm) has been improved for fire danger rating in FOFDESS. In this state, FOFDESS is an integrated system which includes the dimensions of prediction, detection and management. As a result of the experiments, it was found out that FOFDESS helped determining the most accurate strategy for fire fighting by producing effective results. (C) 2011 Elsevier Ltd. All rights reserved.