Partners optimum decision-making of virtual research center based on support vector machine and fuzzy analytic hierarchy process

To solve some problems caused by the information fuzziness and uncertainty in selecting cooperative partner of Virtual Research Center (VRC), a comprehensive decision-making model based on Support Vector Machine and Fuzzy Analytic Hierarchy Process (SVM-FAHP) was proposed. Firstly, the SVM classification model was constructed to classify the data information of partners and the alternative set was reduced after the primary evaluation. Secondly, the judgment matrix was established in trapezoidal fuzzy number and the priority weights of criteria and sub-criteria were calculated. Then, the consistency of judgment matrix was tested in the necessary and sufficient condition of consistency. In the end, the alternatives were ranked with the integration of the fuzzy gravity method. Finally, the partner selection for the Yalong river hydropower development VRC was presented as an example. It was showed that SVM-FAHP model could decrease the inputs of partners' decision-making of VRC and improve classification precision and decision-making efficiency. In addition, the application of the trapezoidal fuzzy number enabled the model to combine qualitative analysis with quantitative analysis effectively, reduced subjective influences and selected the best cooperative partner objectively.