A generic methodology for developing fuzzy decision models
An important paradigm in decision-making models is utility-maximization where most models do not include actors' motives. Fuzzy set theory on the other hand offers a method to simulate human decision-making. However, the literature describing expert-driven fuzzy logic models, rarely gives precise details on the methodology (to be) used. To fill the gap, this paper describes a methodology of 10 steps to model individual actor's drivers, motives, hereby taking into account the ecological, social and economic context. Testing the methodology on the composition of mixed farming systems in the Mekong Delta, Vietnam, showed that manual model development is not a waterfall approach but requires feedback loops, except for model implementation. Using feed-back loops, the proposed 10 step method allowed to include human drivers and motives other than utility-maximization and to maintain a degree of transparency hard to achieve when using automated procedures.
|Keywords||Agriculture, Decision-making, Expert systems, Fuzzy models, Hierarchical models|
|Persistent URL||dx.doi.org/10.1016/j.eswa.2011.07.126, hdl.handle.net/1765/31950|
Bosma, R., van den Berg, J., Kaymak, U., Udo, H., & Verreth, J.. (2012). A generic methodology for developing fuzzy decision models. Expert Systems with Applications, 39(1), 1200–1210. doi:10.1016/j.eswa.2011.07.126