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In decision making, crisp ranking is not possible when the entire attribute characteristics and their degree of importance are known precisely. In real world situations decision making takes place in an environment where the goals, the constraints, and the consequences of possible actions are not known precisely. Thus the best condition for classic decision making problem may not be satisfied when the situation involves both fuzzy and crisp data. Site specific soil fertility and seasonal crop selection data are characterized by high degree of fuzziness and uncertainty. In our model, intuitionistic fuzzy rough set establishes a close connection between the concepts of similarity and dissimilarity thereby providing an excellent framework for ranking soil fertility. Further fuzzy Bayesian incorporates both fuzzy and uncertainty in the probability model yielding more realistic seasonal paddy variety selection. The decision model introduced in this paper is suitable for both data rich and data poor environment. The results illustrate that the soil fertility ranking and successive paddy variety selection can help to sustain the soil fertility in subsequent rotations and minimize the loss of nutrients from the sites.

Site Specific Soil Fertility Ranking and Seasonal Paddy Variety Selection: An Intuitionistic Fuzzy Rough Set and Fuzzy Bayesian Based Decision Model