AGS: a precise and efficient AI-based hybrid software effort estimation model Online publication date: Mon, 14-Dec-2020
by V. Vignaraj Ananth; S. Srinivasan
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 18, No. 1, 2021
Abstract: To predict the amount of effort to develop software is a tedious process for software companies. Hence, predicting the software development effort remains a complex issue drawing in extensive research consideration. The success of software development process considerably depends on proper estimation of effort required to develop that software. Effective software effort estimation techniques enable project managers to schedule software life cycle activities properly. The main objective of this paper is to propose a novel approach in which an artificial intelligence (AI)-based technique, called AGS algorithm, is used to determine the software effort estimation. AGS is hybrid method combining three techniques, namely: adaptive neuro fuzzy inference system (ANFIS), genetic algorithm and satin bower bird optimisation (SBO) algorithm. The performance of the proposed method is assessed using a well standard dataset with real-time benchmark with many attributes. The major metrics used in the performance evaluation are correlation coefficient (CC), kilo lines of code (KLoC) and complexity of the software. The experimental result shows that the prediction accuracy of the proposed model is better than the existing algorithmic models.
Online publication date: Mon, 14-Dec-2020
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Intelligence and Data Mining (IJBIDM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com