Software Cost Estimation using Adaptive Neuro-Fuzzy Inference System

Over the past 30 years, one of the challenges of software engineers and managers of software companies in the development of software projects is to estimate accurate cost, effort, quality and risk analysis. Although over 30 years several models presented by researchers, each of them had their strengths and weaknesses. But the need for new methods to overcome the COCOMO model still exists. During the last 20 years’ models based on Artificial Intelligence have been considered more than other models by researchers which among them, neuro-fuzzy models are the latest model. The aim of this paper is to reduce errors and increase accuracy in estimating the cost and effort in software development. To achieve these goals NASA63 data collection and Adaptive Neuro Fuzzy Inference System (ANFIS) models are used and we could achieve MMRE error in proposed method to 0/0984 and the accuracy of estimate to 0/889.