Development of Intelligent Effort Estimation Model Based on Fuzzy Logic Using Bayesian Networks

Author(s):  
Jahangir Khan ◽  
Zubair A. Shaikh ◽  
Abou Bakar Nauman
2021 ◽  
pp. 10-24
Author(s):  
Jabar Yousif ◽  
Dinesh K. Saini

This paper proposed an Effort Estimation Model for optimizing the deployment of Web Applications Based Fuzzy and Practical Models. Fuzzy logic approach is applied for estimating the development effort, which is compared with practical efforts model in the development process with interpreting the historical data available for the existing functionalities. This paper presented effort estimation model that involves two levels development and requirements for web applications built on three-tier architecture using Microsoft technologies. The first level estimates published by Project Managers and the second level estimates presented by Project Leaders or Developers for any new requirement or enhancements. The model considers the classification of each task as either Low or Medium or High complexity. These tasks pertain to the lowest level parts in bottom-up estimation. Efforts are estimated for designing, coding and unit testing of these tasks and the efforts are summed up to get the effort estimation for the higher level which is a feature to be implemented. The paper also discusses about the application of the effort estimation model by taking a new requirement as a case study. The first level estimates calculated using the effort estimation model has a variance of about 25% when compared with the actual effort. This variance is very much acceptable considering the fact that the first level estimates can be tolerable up to 35%. The proposed effort estimation model would help the project managers to efficiently control the project, manage the resources effectively, and improve the software development process and also trade off analyses among schedule, performance, quality and functionality. Fuzzy logic is used to verify the claims made in efforts estimation. It is proposed a new relation between the number of data and efforts value membership for actual data.


2016 ◽  
Vol 14 (11) ◽  
pp. 233-240
Author(s):  
Song-Hae Kwoak ◽  
Koo-Rack Park ◽  
Dong-Hyun Kim

Estimation of a software cost depends on a probabilistic model and thus it doesn't create precise values. In any case, accessibility of good chronicled information combined with a efficient technique can create improved outcomes. This paper, we have displayed a Software Effort Estimation Model utilizing PSO and Fuzzy Logic. Fuzzy sets have been utilized for displaying uncertainty and imprecision in estimation of effort while PSO has been utilized for tuning parameters. This has been seen from the outcomes that Fuzzy-PSO intelligence gives precise outcomes when compared through its different partners. This system relies upon thinking by linguistic quantifiers and fuzzy logic. This kind of model holds well, when the product plans are communicated by absolute or potentially arithmetical data. Along these lines, this projected methodology improves the old style correlation process that doesn't think about clear cut data. In the fuzzy correlation model, fuzzy sets are used to describe both the clear cut and the arithmetical data.


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