Research Article

Forest Fire Prevention, Detection, and Fighting Based on Fuzzy Logic and Wireless Sensor Networks

Table 10

Fuzzy values obtained by the fuzzifier.

ā€‰ Variable Value Fuzzy values Variable Value Fuzzy value

1 41,6 High(84%),Extreme (15%) Av. 37 High(100%)
39 Low(59%),Normal(40%) Av. 46 Normal(100%)
55 High(74%), Medium(25%) Av. 30 Medium(100%)
10 Medium(100%) Av. 9,5 Medium(100%)
16,5 Low (100%) Av. 18 Normal(33%),Low(66%)
876 High(12%),Extreme(87%) Av. 592 High(100%)
47,8 Extreme(77%), High(22%) Av. 13,6 Medium(79%),High(20%)

2 28 Low(40%), Medium(60%) Av. 25 Low(100%)
57 Normal(100%) Av. 54 Normal(100%)
23 Low(35%),Medium(64%) Av. 25 Low(24%),Medium(75%)
14,7 Medium(32%),High(67%) Av. 12 Medium(100%)
21 Normal(100%) Av. 20 Normal(100%)
ā€‰ 395 Normal(100%) Av. 350 Normal(100%)
10 Medium(100%) Av. 7 Medium(69%),Normal(30%)

3 22 Low(100%) Av. 22,2 Low(100%)
63,19 Normal(54%),High(45%) Av. 64,42 Normal(55%),High(44%)
7,5 Low(100%) Av. 9,5 Low(100%)
28,83 High(100%) Av. 32,52 High(74%), Extreme(25%)
19,1 Normal(69%),Low(30%) Av. 21,35 Normal(100%)
546 High(100%) Av. 454 Normal(46%), High(53%)
17,61 Medium(29%),High(70%) Av. 1,47 Normal(85%),Medium(14%)