Fuzzy regression for weight information extraction in fuzzy environment

Arbaiy, Nureize (2014) Fuzzy regression for weight information extraction in fuzzy environment. In: Knowledge Management International Conference (KMICe 2014), 12-15 August 2014, Langkawi, Malaysia.

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Abstract

Extracting new information is one of the knowledge management ability yet difficult in environment which contains fuzzy information. For example. measuring a product's quality is an important task which normally requires visual inspection basis. and this grading is subject to expert knowledge and interpretation. Apparently. fuzzy information is inherently included in this evaluation and an appropriate tool is necessary to manage such information. Thus. to assist the uncertain situation. in this paper. a fuzzy regression is introduced to improve the extraction of attribute's weight in a multi-attribute decision making. The proposed model will manage the linguistic assessment provided by evaluators in order to compute collective assessments about the product samples. The proposed model is applied to milled rice grading, as the quality inspection process requires a method to ensure product quality. We include simulation results and highlight the advantage 01' the proposed method in handling the existence oP fuzzy information and managing the information which comes from such uncertain environment.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:fuzzy regression analysis; multi-attribute; attributes weighting; decision making
Subjects:Q Science > QA Mathematics > QA273 Probabilities. Mathematical statistics
Divisions:Faculty of Computer Science and Information Technology > Department of Software Engineering
ID Code:5847
Deposited By:Normajihan Abd. Rahman
Deposited On:03 Nov 2014 16:07
Last Modified:03 Nov 2014 16:07

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