NDLI: Application of granular fuzzy modeling for abstracting labour productivity knowledge bases

Content Provider	IEEE Xplore Digital Library
Author	Tsehayae, A.A. Pedrycz, W. Fayek, A.R.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Univ. of Alberta, Edmonton, AB, Canada (Pedrycz, W.) \|\| Dept. of Civil & Environ. Eng., Univ. of Alberta, Edmonton, AB, Canada (Tsehayae, A.A.; Fayek, A.R.)
Abstract	Construction labour productivity is a cost efficiency measure of crews in producing outputs usually at an activity level. The relationship between the factors affecting the efficiency of crews and the achieved labour productivity is being studied using various stand-alone modeling approaches like regression analysis, neural networks, and fuzzy logic-based expert systems. However, the developed models suit only a specific context and most importantly, a method for transferring and generalizing the knowledge captured in the various models has not yet been fully developed. This paper presents the application of a granular fuzzy modeling approach for transferring captured knowledge and the process of developing a granular generalized construction labour productivity model having an improved prediction capability. The granular fuzzy model abstracts three construction productivity models dealing with industrial welding activities using a case-based reasoning approach on clusters of the respective model input data prototypes. The performance of the model is evaluated using coverage and specificity plots and different model parameters are optimized.
Sponsorship	IEEE
Starting Page	1096
Ending Page	1101
File Size	571634
Page Count	6
File Format	PDF
ISBN	9781479903481
DOI	10.1109/IFSA-NAFIPS.2013.6608553
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-24
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data models Prototypes Welding Input variables Context modeling Computational modeling Numerical models construction labour productivity information granules knowledge management
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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