Ismail, Zuhaimy (2006) Mathematical and statistical modelling in solving industrial problems - a university industrial collaborative research. In: Proceedings of Annual Fundamental Science Seminar 2006 (AFSS 2006), 6th - 7th June 2006, Universiti Teknologi Malaysia, Skudai, Malaysia.
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Abstract
Successful business requires good management, decision making and planning process. Strong bridges are required to connect theory (the university) and practice (industry), and many problems must be solved before mathematical models or methods can be used efficiently and effectively in management situations. Application issues are rather under explored and this has been highlighted in many papers publication and it is virtually impossible to work with real organisations without realising that the gap between the development of mathematical models and their application is huge. In this paper, we present case studies on modelling of palm oil yield and forecasting of electricity demand where collaboration between university and industry may be carried out. Here we did not explore the technical aspects of demand forecasting but rather to highlight the need for benchmarking the forecasting practices when conducting forecast of electricity demand. This applies to to the application of mathematical model for predicting palm oil yeild.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Excellence in R & D through advancement in fundamental sciences |
Uncontrolled Keywords: | forecasting, extrapolation method, genetic algorithms, energy, industrial partnership |
Subjects: | Q Science > QA Mathematics |
Divisions: | Science |
ID Code: | 10871 |
Deposited By: | Zalinda Shuratman |
Deposited On: | 11 Nov 2010 07:21 |
Last Modified: | 19 Oct 2017 00:42 |
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