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

被引：27
作者：
Elmas, Cetin [2 ]
Sonmez, Yusuf [1 ]
机构：
[1] Gazi Univ, Dept Elect Technol, Gazi Vocat Coll, TR-06760 Ankara, Turkey
[2] Gazi Univ, Dept Elect Educ, Tech Educ Fac, TR-06500 Ankara, Turkey
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2011年 / 38卷 / 08期
关键词：
Detection and prediction of forest fire; Artificial Neural Network; Naive Bayes Classifier; Fuzzy Switching; Decision Support System; INTELLIGENT SYSTEM; NEURAL-NETWORKS;
D O I：
10.1016/j.eswa.2011.01.125
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：9225 / 9236
页数：12
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