Intelligence-Software Cost Estimation Model for Optimizing Project Management
subject: Cost estimation; Deep learning; Intelligence; Machine learning; Predictive; Software cost; Uncertainty
description: With the evolution of pervasive and ubiquitous application, the rise of web-based application as well as its components is quite rising as such applications are used both for development and analysis of the web component by developers. The estimation of software cost is controlled by multiple factors right from human-driven to process driven. Most importantly, some of the factors are never even can be guessed. At present, there are no records of literature to offer a robust cost estimation model to address this problem. Therefore, the proposed system introduces an intellectual model of software cost model that is mainly targets to perform optimization of entire cost estimation modeling by incorporating predictive approach. Powered by deep learning approach, the outcome of the proposed model is found to be cost effective in comparison to existing cost estimation modeling. 2019, Springer Nature Switzerland AG.
creator: Naik P.; Nayak S.
source: Advances in Intelligent Systems and Computing, Vol-984, pp. 433-443.
publisher: Springer Verlag
date: 2019-01-01
rights: Restricted Access
relation: ISSN: 21945357; ISBN: 978-303019806-0
format: Online
language: English
type: Conference paper
coverage: Naik P., Research Scholar VTU, Department of Computer Science and Engineering, Faculty of Engineering, CHRIST (Deemed to be University), Bangalore, India; Nayak S., Department of Information Science and Engineering, RV College of Engineering, Bangalore, India