Applying ARIMA and Fuzzy Logic to Predict the Electricity Spare Parts Demand

Abstract:

With the development of power industry and the growth of high-voltage power equipments in electric power company, the supply and management of spare parts are becoming more complexity and onerous. This investigation proposed a hybrid method to effectively predict the requirements of electric spare parts utilizing fuzzy logic and ARIMA so as to provide as a reference of spare parts control. The forecasting methods are tested in an empirical, comparative study for an electric power company of China. The results show that the approach is one of the most accurate methods.

• Periodical: Advanced Materials Research (Volumes 734-737)
• Pages: 1728-1733
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.734-737.1728
• Online since: August 2013
• Authors: Yu Kun Cao, Yun Feng Li
• Keywords: Arima, Fuzzy Logic, Prediction Algorithm, Spare Parts, Time Series Model

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