A Hybrid Fuzzy-Ann Approach for Software Effort Estimation

Abstract

Software development effort estimation is one of the major activities in software project management. During the project proposal stage there is high probability of estimates being made inaccurate but later on this inaccuracy decreases. In the field of software development there are certain matrices, based on which the effort estimation is being made. Till date various methods has been proposed for software effort estimation, of which the non algorithmic methods, like artificial intelligence techniques have been very successful. A Hybrid Fuzzy-ANN model, known as Adaptive Neuro Fuzzy Inference System (ANFIS) is more suitable in such situations. The present paper is concerned with developing software effort estimation model based on ANFIS. The present study evaluates the efficiency of the proposed ANFIS model, for which COCOMO81 datasets has been used. The result so obtained has been compared with Artificial Neural Network (ANN) and Intermediate COCOCMO model developed by Boehm. The results were analyzed using Magnitude of Relative Error (MRE) and Root Mean Square Error (RMSE). It is observed that the ANFIS provided better results than ANN and COCOMO model.