ANN with Fuzzification in Software Cost Estimation

ANN with Fuzzification in Software Cost Estimation

This paper tries to provide a prototype for cost estimation with fuzzification and ANN, which is a propositional calculus based on functional point of the training data set. These kind of solutions are regardless of mathematical views of the problem and it is useful for such case which does not have precise inputs, for instance in software cost estimation. There are methods in four major categories such as algorithmic COCOMO-II (Constructive Cost Model) model, functional point, analogy, expert judgment, top down and bottom down method which have their own pros and cons. Their merits will be discussed in comparison with the proposed methodology of ANN BP (Artificial Neural Network Back Propogation) and fuzzy logic; in order to achieve their more gain in estimation. It will lead us to know that which method should be used with specific conditions.

Author(s) Details

Dinesh Bhagwan Hanchate
Department of Computer Engineering, VP’s KBIET, Baramati, Pune, India.

Mahsa Hassankashi
Department of Computer Science and Engineering, Ovidius GmbH, Berlin, Germany.

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