Fuzzy random regression to improve coefficient estimation for Malaysian Agricultural Industry

Conventional model setting of production planning is developed with numerical crisp values. Additionally coefficient values must be determined before the model is set. It is however troublesome and complex for decision maker to provide rigid values and determining the coefficient values for the model. Building the production planning model with precise values sometimes generates improper solution. Hence, this study proposes a fuzzy random regression method to estimate the coefficient values for which statistical data contains simultaneous fuzzy random information. A numerical example illustrates the proposed solution approach whereby coefficient values are successfully deduce from the statistical data and the fuzziness and randomness were treated based on the property of fuzzy random regression. The implementation of the fuzzy random regression method shows the significant capabilities to estimate the coefficient value to further improve the model setting of production planning problem which retain the simultaneous uncertainties.

Name dc:type.qualificationname

mphil

Level dc:type.qualificationlevel

masters

Grantor dc:publisher.institution

Universiti Tun Hussein Onn Malaysia

Year dc:date.issued

2014

Author dc:creator

• Mohd Rahman, Hamijah

• QA Mathematics
• QA299.6-433 Analysis

Language dc:language

en