A novel PSO based approach with hybrid of fuzzy C-means and learning automata in software cost estimation

Abstract

We used Particle Swarm Optimization (PSO) algorithm hybrid with Fuzzy C-Means (FCM) and Learning Automata (LA) algorithms for Software Cost Estimation (SCE). In this paper we test and evaluate PSO-FCM and PSO-LA hybrid models on NASA dataset software projects. The obtained results showed that in the hybrid models the values of Magnitude of Relative Error (MRE) and Mean Magnitude of Relative Error (MMRE) were reduced compared with COCOMO model and also the accuracy of Percentage of Relative Error Deviation (PRED) was higher in the hybrid models.