Indian Journal of Science and Technology

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A Novel PSO Based Approach with Hybrid of Fuzzy C-means and Learning Automata in Software Cost Estimation


Affiliations
1 Department of Computer Engineering, Science and Research Branch, Islamic Azad University, West Azerbaijan, Iran, Islamic Republic of
 

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.

Keywords

COCOMO Model, Fuzzy C-means, Learning Automata, Particle Swarm Optimization, Software Cost Estimation
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  • A Novel PSO Based Approach with Hybrid of Fuzzy C-means and Learning Automata in Software Cost Estimation

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Authors

Farhad Soleimanian Gharehchopogh
Department of Computer Engineering, Science and Research Branch, Islamic Azad University, West Azerbaijan, Iran, Islamic Republic of
Laya Ebrahimi
Department of Computer Engineering, Science and Research Branch, Islamic Azad University, West Azerbaijan, Iran, Islamic Republic of
Isa Maleki
Department of Computer Engineering, Science and Research Branch, Islamic Azad University, West Azerbaijan, Iran, Islamic Republic of
Saman Joudati Gourabi
Department of Computer Engineering, Science and Research Branch, Islamic Azad University, West Azerbaijan, Iran, Islamic Republic of

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.

Keywords


COCOMO Model, Fuzzy C-means, Learning Automata, Particle Swarm Optimization, Software Cost Estimation



DOI: https://doi.org/10.17485/ijst%2F2014%2Fv7i6%2F54331