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Software Effort Estimation Using Particle Swarm Optimization with Inertia Weight
CH V M K HARI, Prasad Reddy.P.V.G.D
Pages - 87 - 96     |    Revised - 01-09-2011     |    Published - 05-10-2011
Volume - 2   Issue - 4    |    Publication Date - September / October 2011  Table of Contents
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KEYWORDS
Software Effort Estimation, Software Cost Estimation, Particle Swarm Optimization
ABSTRACT
Software is the most expensive element of virtually all computer based systems. For complex custom systems, a large effort estimation error can make the difference between profit and loss. Cost (Effort) Overruns can be disastrous for the developer. The basic input for the effort estimation is size of project. A number of models have been proposed to construct a relation between software size and Effort; however we still have problems for effort estimation because of uncertainty existing in the input information. Accurate software effort estimation is a challenge in Industry. In this paper we are proposing three software effort estimation models by using soft computing techniques: Particle Swarm Optimization with inertia weight for tuning effort parameters. The performance of the developed models was tested by NASA software project dataset. The developed models were able to provide good estimation capabilities.
CITED BY (1)  
1 Sandhu, G. S., & Salaria, D. S. (2014). A Bayesian Network Model of the Particle Swarm Optimization for Software Effort Estimation. International Journal of Computer Applications, 96(4).
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Mr. CH V M K HARI
Gitam University - India
kurmahari@gmail.com
Mr. Prasad Reddy.P.V.G.D
- India