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.