A Novel Fuzzy Model for Software Cost Estimation

Abstract

It predicts the estimated cost at beginning periods of development life cycle is a challenging assignment for the powerful management of any software industry. This model essentially considered on the significance of the datasets was utilized for analysis, kinds of intelligence and Fuzzy Logic were applied to foresee estimated cost lastly, execution assessed of prediction methods. From our model, we found that the COCOMO dataset is the most conspicuous dataset, trailed by NASA, and DESHARNAIS dataset. The MARE and MMRE are noticeable execution assessment methods in the field of study. Further, we found that the Neural Networks technique was repetitively utilized when contrasted with different models pursued by the Hybrid techniques, at that point Fuzzy Logic, Decision Tree and Evolution Computation in a specific order. This model is serving to incredible for research apprentices in the arena of software cost Estimation.