Learn the Ranking of Precedence Cases1
نویسنده
چکیده
A modification of a fuzzy classification algorithm is shown in this paper. This algorithm classifies multiple-criteria fuzzy or crisp elements and the task of the classification is traced back to ranking of elements, as well as to learning weight numbers similarly to neural networks. Two new particular versions of the algorithm can be utilized in the multiple-criteria decision-making. If we have precedence alternatives (cases), the algorithm is able to learn the ranking of alternatives when the criteria and the sequence of alternatives are known. The ready classifiers may be used as evaluating programs and further alternatives can be listed among the precedence alternatives with their help.
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