Trust evaluation model of partners in complex products and systems based on Rough Set theory and Support Vector Machine

Facing the problems of so many decision attributes and few data samples for decision-making analysis when the integrators in complex products and systems evaluate the partners of collaboration and innovation, this paper creates a trust evaluation model of collaborative partners in CoPS based on rough set and (RS) Support Vector Machines (SVM). In this paper, firstly, trust evaluation system about partners of collaboration and innovation will be set up in CoPS. Secondly, followed by the application of RS attribute reduction as a data pre-processing removes the redundancy in the decision-making property, and then combined with support vector machines in dealing with small samples, as well as non-linear question on the basis of trust in the advantages of the classification of the partners, in that it will not reduce the classification performance achieved under the premise of reducing data dimensionality and classification of the complexity of the process of purpose to help decision-makers to achieve the confidence of partners in collaborative innovation evaluation and chosen. Finally, the method has been applied to complex systems integration products supplier to the trust of the assessment process in detail for the actual operation of the method steps and preliminary verification of the validity of the model.