Estimating software development effort using fuzzy clustering‐based analogy-Reference-Cited by-同舟云学术

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Estimating software development effort using fuzzy clustering‐based analogy

Published:2020-10-13 Issue:4 Volume:33 Page:
ISSN:2047-7473
Container-title:Journal of Software: Evolution and Process
language:en
Short-container-title:J Softw Evol Proc

Author:

Amazal Fatima Azzahra¹^ORCID,Idri Ali²³^ORCID

Affiliation:

1. LabSIV, Department of Computer Science, Faculty of Science Ibn Zohr University Agadir Morocco

2. Software Projects Management Research Team, ENSIAS Mohamed V University Rabat Morocco

3. Complex Systems Engineering and Human Systems Mohammed VI Polytechnic University Ben Guerir Morocco

Publisher

Wiley

Subject

Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/smr.2324

Reference69 articles.

1. Software effort estimation as a multiobjective learning problem

2. An investigation of artificial neural networks based prediction systems in software project management

3. Expert judgement as an estimating method

4. MendesE.The use of Bayesian networks for web effort estimation: further investigation. In: Proceedings of the Eighth International Conference on Web Engineering (ICWE'08). Yorktown Heights NJ (USA);2008:203–216.

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Software effort estimation using convolutional neural network and fuzzy clustering;Neural Computing and Applications;2024-05-07

2. MFLion‐DMN: Mayfly Lion‐optimized deep maxout network for prediction of software development effort;Journal of Software: Evolution and Process;2024-02-28

3. Using Standard Deviation with Analogy-Based Estimation for Improved Software Effort Prediction;KSII Transactions on Internet and Information Systems;2023-05-31

4. Evolution of Software Development Effort and Cost Estimation Techniques: Five Decades Study Using Automated Text Mining Approach;Mathematical Problems in Engineering;2022-05-02

5. Efficient Analogy-based Software Effort Estimation using ANOVA Convolutional Neural Network in Software Project Management;Smart Intelligent Computing and Applications, Volume 1;2022

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