Agricultural Machinery Spare Parts Demand Forecast Based on BP Neural Network

Abstract:

With the rapid development of agricultural machinery, forecasting the demand for spare parts is essential to ensure timely maintenance of agricultural machinery. Based on features of spare parts, BP neural network is chosen to forecast the demand. First, this paper analyzes factors that affect the demand for spare parts. Second, steps and processes of neural network prediction are described. The third part of this paper is case study based on certain brand of agricultural machinery spare parts. BP neural network turns out suitable for forecasting the demand for spare parts.

• Periodical: Applied Mechanics and Materials (Volumes 635-637)
• Pages: 1822-1825
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.635-637.1822
• Online since: September 2014
• Authors: Yao Guang Hu, Shuo Sun, Jing Qian Wen*
• Keywords: Agricultural Machinery, Demand Forecast, Neural Network (NN), Spare Parts

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