Abstract

This paper will present a comprehensive overview of the use of fuzzy logic approach in modeling as a decision support tool for cost estimation. The model is based on expectation-maximisation (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models. The clusters given by the EM algorithm has lead to the development of fuzzy rules. The best fuzzy logic model was found to consist of two fuzzy rules. The result also indicates that kind of behavior given by the EM clustering algorithm has reduced the uncertainty of estimate, which in turn the accuracy of the estimate is improved.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.