Improving the Consistency of AHP Matrices Using a Multi-layer Perceptron-Based Model
作者： Jose Antonio Gomez-Ruiz , Marcelo Karanik , José Ignacio Peláez
DOI: 10.1007/978-3-642-02478-8_6
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摘要: The Analytic Hierarchy Process (AHP) uses hierarchical structures to arrange comparing criteria and alternatives in order give support decision making tasks. comparisons are realized using pairwise matrices which filled according the maker criterion. Then, matrix consistency is tested priorities of obtained. If a incomplete, two procedures must be realized: first, complete with adequate values for missing entries and, second, improve an acceptable level. In this paper model based on Multi-layer Perceptron (MLP) neural networks presented. This capable completing AHP improving its at same time.
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