I am thinking about using Fuzzy logic to model the decision making process of an individual and I would be interested in hearing your comments with regards to my plan. I must state that I have not used Fuzzy logic before.
The problem is that I am trying to emulate the decision making process of a driver as to weather or not to recharge his electric car. So he arrives at his destination and to keep it simple there are two factors influencing his decision (1) the state of charge of the battery and (2) the time that he will be parked for.
I have recorded the following data from actual electric cars, (1) the state of charge of the cars as they arrive at the destination (2) the time spent parked and (3) weather they charged the car or not. I was intending on using this data to train the system.
My main question is, would an adaptive neuro-fuzzy inference system (ANFIS) be suitable for this this? Could you offer an suggestions as to things I should do make the system operate correctly or things to watch out for?
Appreciate and suggestions
[Merged information from duplicate Question]
I have read in the documentation that "output membership functions are only linear or constant for Sugeno-type fuzzy inference". What implications would this have for my problem?