Incorporating whale optimization algorithm with deep belief network for software development effort estimation

Anupama Kaushik (), Niyati Singal and Malvika Prasad
Additional contact information
Anupama Kaushik: Maharaja Surajmal Institute of Technology
Niyati Singal: Maharaja Surajmal Institute of Technology
Malvika Prasad: Maharaja Surajmal Institute of Technology

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 4, No 8, 1637-1651

Abstract: Abstract The software industry is highly competitive, and hence, it is imperative to have an accurate method to estimate the effort needed in the key phases of software development. Accurate estimates ensure efficient allocation of human and machine resources for the project. This paper proposes a technique for software development effort estimation using deep belief network (DBN). For fine-tuning of DBN, Whale Optimization Algorithm (WOA) is used which mimics the social behaviour of humpback whales. The proposed technique DBN-WOA has been experimentally evaluated on four promise datasets—COCOMO81, NASA93, MAXWELL and CHINA. The results from DBN-WOA are compared with the results from fine-tuning of DBN with backpropagation (DBN-BP) and it is observed that the proposed technique outscores DBN-BP. The proposed approach is also empirically validated through a statistical framework.

Keywords: Software development effort estimation; Deep belief network; Backpropagation; Whale optimization algorithm; Metaheuristics; Neural networks (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13198-021-01519-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ijsaem:v:13:y:2022:i:4:d:10.1007_s13198-021-01519-8

Ordering information: This journal article can be ordered from
http://www.springer.com/engineering/journal/13198

DOI: 10.1007/s13198-021-01519-8

Access Statistics for this article

International Journal of System Assurance Engineering and Management is currently edited by P.K. Kapur, A.K. Verma and U. Kumar

More articles in International Journal of System Assurance Engineering and Management from Springer, The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().