A Portfolio Model of Faculty Members using Adaptive Neuro-Fuzzy Inference System

In this research, the portfolio of faculty members has been formed and their evaluation from two dimensions of performance and potential has been done using the human resources matrix. In terms of performance; Education and research variables and in the dimension of potential; The variables of ability, aspirations and engagement are considered. Educational and research performance were collected in collaboration with the Office of Monitoring and Evaluation, Quality Assurance and the Vice Chancellor for Research, respectively, also valid evaluation forms and standard questionnaires have been used to evaluate the potential of faculty members. According to the purposive sampling method, 110 faculty members were evaluated and monitored. MATLAB software (R2018b, v9) and neural-fuzzy network method have been used for modeling and data analysis. Finally, faculty members with two scenarios of classical logic (binary or Aristotelian (0 and 1)) and fuzzy logic into four parts of the matrix, which are; Stars, core employees, question marks and dead woods were marked. According to the obtained outputs, about 30% of the subjects were in the star section, 21% as core employees, 16% as question marks and 33% in the dead woods section. Finally, by comparing the classical and fuzzy logics, the advantages of using this method are described. The obtained results indicate the success of the proposed method in analyzing the function of faculty members in the university in question and can play a role in the major decisions of that university.