Analyzing Semiconductor component's market sales data to create an Expert Fuzzy inference system

Saljooghi, Saeed and Safisamghabadib, Azamdokht (2016): Analyzing Semiconductor component's market sales data to create an Expert Fuzzy inference system. Published in: International Academic Journal of Science and Engineering , Vol. 3, No. 6 : pp. 185-198.

Abstract

The Policy for buying chips is determined from Original Equipment Manufacturer (OEM's) laptops and computers through similarity criteria and probability rules. This study aims to create expert system that is prediction of purchase behavior in Semiconductor market. similarity criteria and probability rules are extracted from Quarterly list OEM's Information Order in Semiconductor market. we analyze and extract rules form OEM purchase behavior data by Data collection and statistical methods of data mining and then convert them into Fuzzy sets. In addition to information received from market nature, we create an expert system for deduction. our analysis of similar products show that there is two major groups of OEM in purchasing similar products That restoration information is done for a period of one year by using probability rules and getting approximately 95% of average score quarterly.

• Item Type: MPRA Paper
• Language: English
• Keywords: expert system, probability rules, semiconductor market, similarity size, fuzzy inference
• Subjects: C - Mathematical and Quantitative Methods > C0 - General; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling

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