I have to use fuzzy to find the likelihood of a fire in a car based on the following conditions, The judgment set are as follows: u1—(0.5,0.3,0.1,0.1)Likelihood of a fire occurring while charging a car u2—(0.3,0.2,0.2,0.3)The evaluation set for a car crash fire u3—( 0 ,0.1,0.4,0.5)The judgment set for a car flooding fire u4—(0.4,0.4,0.1,0.1)The critical set affected and ignited
which means – considering u1 - Likelihood of a fire while charging a car, 50% said it's big, 30% said it was larger, 10% said it was average, 10% said it's small same for u2,u3 and u4
The evaluation set of these four factors is composed of the evaluation matrix:
The fuzzy comprehensive decision-making model of fire risk of new energy vehicles is as follows:
Due to the 0.5+0.3+0.2+0.2=1.2,In order to find the percentage, the normalization process is performed, namely:
It can be seen from the formula that the comprehensive decision of the four factors affecting the new energy vehicle fire is as follows: 41% people think such accidents are very dangerous, 25% people think relatively dangerous, 17% people think the danger is average, and 17% people think there is no danger.
The above is my question to solve, I have opened fuzzy interface and created 4 inputs Then my doubts are What type of membership function MF type is suitable for this problem, shall i use gaussianmf ? Also have doubt in how to give inputs based on these conditions - like How many MFs (membership functions should i give) What value range shoud i give in params How to set the rules? What is their weight value I should assign? How many outputs should i give, is it one or four I have referred a video on Getting Started with Fuzzy Logic Toolbox, but i'm still not clear to how to solve the problem. I would be of great help if someone could really assist me in solving this?