Current and Future Developments in Artificial Intelligence

Current and Future Developments in Artificial Intelligence

Intelligent Computational Systems: A Multi-Disciplinary Perspective

Intelligent Computational Systems presents current and future developments in intelligent computational systems in a multi-disciplinary context. Readers will learn about the pervasive and ubiquitous ...
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P-UTADIS: A Multi Criteria Classification Method

Pp. 214-267 (54)

Majid Esmaelian, Hadi Shahmoradi and Fateme Nemati


In this chapter, a new multi criteria classification technique is presented. This method is a developed/advanced UTilites Additives DIScriminantes (UTADIS) method which applies a polynomial function as its utility function for each attribute rather than a piecewise linear approximation. The method, named P-UTADIS, is applied for both nominal and ordinal group and by calculating coefficients of polynomials, threshold limits of classes and weights of attributes, tends to minimize the classification errors. Unknown parameters of a classification problem are estimated through a hybrid algorithm including Particle Swarm Optimization algorithm (PSO) and Genetic Algorithm (GA). The results of implementing P-UTADIS on different data sets and comparing them with some other previous methods indicate the high efficiency of P-UTADIS.


Classification, Genetic algorithm, PSO algorithm, UTADIS method, Utility function.


Department of Management, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, Iran.