Tuning Function Point Analysis Model by Using Fuzzy Neural Network
نویسنده
چکیده
Estimation of the size and time required for software development is probably the most difficult task of software projects development. Functional Point Analysis (FPA) model are gaining a wide popularity for assessing software size. By the definition of Function Point Analysis model, all 14 General System Characteristics (GSC) are not totally independent. A fuzzy neural network model for tuning the GSCs is presented in this paper. This model has a distinguishing feature in that it can express complex nonlinear GSC linguistically. Using the fuzzy rules and tuning the connection weights of this model, we can find the optimalized connection weights through learning process. With these optimal connection weights, the estimator can estimating software size more accurated.
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