A New Architecture Based on Artificial Neural Network and PSO Algorithm for Estimating Software Development Effort


  • Amin Moradbeiky Islamic Azad University, Kerman Branch, Kerman, Iran
  • Amid Khatibi Bardsiri Islamic Azad University, Kerman Branch, Kerman, Iran


Development Effort Estimation, Neural Networks, Particle Swarm Optimization, Software Project,


Software project management has always faced challenges that have often had a great impact on the outcome of projects in future. For this, Managers of software projects always seek solutions against challenges. The implementation of unguaranteed approaches or mere personal experiences by managers does not necessarily suffice for solving the problems. Therefore, the management area of software projects requires tools and means helping software project managers confront with challenges. The estimation of effort required for software development is among such important challenges. In this study, a neural-network-based architecture has been proposed that makes use of PSO algorithm to increase its accuracy in estimating software development effort. The architecture suggested here has been tested by several datasets. Furthermore, similar experiments were done on the datasets using various widely used methods in estimating software development. The results showed the accuracy of the proposed model. The results of this research have applications for researchers of software engineering and data mining.


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How to Cite

Moradbeiky, A., & Bardsiri, A. K. (2017). A New Architecture Based on Artificial Neural Network and PSO Algorithm for Estimating Software Development Effort. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(4), 13–17. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1590