Mohammad Saber Iraji

Work place: Faculty Member of Department of Computer Engineering and Information Technology, Payame Noor University, I.R. of Iran



Research Interests: Data Mining, Image Processing, Artificial Intelligence, Software Engineering


Mohammad Saber Iraji received B.Sc in computer software engineering from shomal university, Iran, amol;M.Sc1 in industrial engineering (system management and productivity) from khatam university Iran ,Tehran and M.Sc2 in computer science from Islamic azad university , sari branch . Currently, he is engaged in research and teaching on computer graphics, image processing , fuzzy and artificial intelligent , data mining, software engineering.

Author Articles
Students Classification With Adaptive Neuro Fuzzy

By Mohammad Saber Iraji Majid Aboutalebi Naghi. R. Seyedaghaee Azam Tosinia

DOI:, Pub. Date: 8 Jul. 2012

Identifying exceptional students for scholarships is an essential part of the admissions process in undergraduate and postgraduate institutions, and identifying weak students who are likely to fail is also important for allocating limited tutoring resources. In this article, we have tried to design an intelligent system which can separate and classify student according to learning factor and performance. a system is proposed through Lvq networks methods, anfis method to separate these student on learning factor . In our proposed system, adaptive fuzzy neural network(anfis) has less error and can be used as an effective alternative system for classifying students.

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Object Oriented Software Effort Estimate with Adaptive Neuro Fuzzy use Case Size Point(ANFUSP)

By Mohammad Saber Iraji Homayun Motameni

DOI:, Pub. Date: 8 Jun. 2012

Use case size point (USP) method has been proposed to estimate object oriented software development effort in early phase of software project and used in a lot of software organizations. Intuitively, USP is measured by counting the number of actors, preconditions, post conditions, scenarios included in use case models. In this paper have presented a Adaptive fuzzy Neural Network model to estimate the effort of object oriented software using Use Case size Point approach. In our proposed system adaptive neural network fuzzy use case size point has less error and system worked more accurate and appropriative than prior methods.

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Other Articles