Bahram Izadi

Work place: Department of Management, Faculty of Administrative Sciences and economics, University of Isfahan, IRAN



Research Interests: Business


Bahram Izadi received his B.S in Applied Physics from University of Isfahan, Iran in 1986. He completed his Master in Business Administration at the same university in 2009 and passed entrance exams for PHD of Marketing Management at University of Isfahan in the same year. He is currently working on his dissertation in the area of E-market segmentation. His area of interest includes E-Business and E-Marketing.

Author Articles
Performance Analysis of Classification Methods and Alternative Linear Programming Integrated with Fuzzy Delphi Feature Selection

By Bahram Izadi Bahram Ranjbarian Saeedeh Ketabi Faria Nassiri-Mofakham

DOI:, Pub. Date: 8 Sep. 2013

Among various statistical and data mining discriminant analysis proposed so far for group classification, linear programming discriminant analysis have recently attracted the researchers’ interest. This study evaluates multi-group discriminant linear programming (MDLP) for classification problems against well-known methods such as neural networks, support vector machine, and so on. MDLP is less complex compared to other methods and does not suffer from local optima. However, sometimes classification becomes infeasible due to insufficient data in databases such as in the case of an Internet Service Provider (ISP) small and medium-sized market considered in this research. This study proposes a fuzzy Delphi method to select and gather required data. The results show that the performance of MDLP is better than other methods with respect to correct classification, at least for small and medium-sized datasets.

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Developing a Virtual Group Decision Support System Based on Fuzzy Hybrid MCDM Approach

By Bahram Izadi Saeedeh Ketabi

DOI:, Pub. Date: 8 Jan. 2013

Organizational decisions involve with unusually vague and conflicting criteria. This controversy increases empirical uncertainties, disputes, and the resulting consequences of these decisions. One possible method in subduing this problem is to apply quantitative approaches to provide a transparent process for resolute conclusions which enables decision makers to formulate accurate and decisive on time decisions. Although numerous methods are presented in the literature, the majority of them aim to develop theoretical models. However, this article aims to develop and implement an integrated fuzzy virtual MCDM model based on fuzzy AHP and fuzzy TOPSIS as a decision support system (DDS). Preventing disadvantageous face-to-face decision-making by achieving positive benefit from virtual decision making causes the proposed DDS to be suitable for making crucial decisions such as supplier selection, employee selection, employee appraisal, R&D project selection, etc. The proposed DDS has been implemented in an optical company in Iran.

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