Application of Chaotic Increasing Linear Inertia Weight and Diversity Improved Particle Swarm Optimization to Predict Accurate Software Cost Estimation

Abstract

Nowadays usage of software products is increases exponential in different areas in society, accordingly, the development of software products as well increases by the software organizations, but they are unable to focus to predict effective techniques for planning resources, reliable design, and estimation of time, budget, and high quality at the preliminary phase of the development of the product lifecycle. Consequently, it delivered improper software products. Hence, a customer loses the money, time, and not belief on the company as well as effort of teamwork will be lost. We need an efficient and effective accurate effort estimation procedure. In the past, several authors have introduced different methods for effort of estimation of the software. Particle Swarm Optimization is a most popular optimization technique. Maintaining diversity in particle swarm optimization is the main challenging one and in this paper, we propose chaotic linear increasing inertia weight and diversity improved mechanism to enhance the diversity. Seven standard data sets were employed to analyze of performance of the proposed technique, and it is outperformed compared to the previous techniques.