The Vehicle Adjustable Suspension System Based on Data Mining

Abstract:

One being developed vehicle adjustable suspension system, need to predict pavement condition then automatically adjust each suspension height, in order to ensure control accuracy and ride comfort. This paper proposed a method using BP neural network to predict the vehicle height sensor data of each wheel suspension. The experimental results show that, the proposed algorithm is practical and reliable, and good outcome have been achieved in the application of instruction carriage.

• Periodical: Applied Mechanics and Materials (Volumes 416-417)
• Pages: 790-795
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.416-417.790
• Online since: September 2013
• Authors: Gu Xiong Li, Kai Huang, Kan Feng Huang
• Keywords: Adjustable Suspension System, BP Neural Network (BPNN), Data Mining (DM)

References

[1] Ding Hao. Data mining technology for securities analysis . Wuhan: Wuhan University of Technology, (2011).

[2] Fang Fugui. Data warehouse and data mining on the projects . Information System, 2012, 18 (2): 49-52.

[3] Zeng Huiqin. Data mining research on information system of relay protection and fault treatment . Guangxi: Guangxi University, (2011).

[4] Li Qiudan. Research and platform realization of data mining algorithms . Dalian: Dalian University of Technology, (2012).

[5] Tu Jin, Data mining based on the simulated annealing algorithm . Chongqing: Chongqing University, (2010).

[6] Wang Yu. The relations and the security problem between data warehouse and data mining . Computer Technology and Development, 2011, 36 (6): 24-32.

[7] Ding Yuanming. Application of data mining technology in teaching quality evaluation . Shanghai: East China Normal University, (2011).

[8] Chen Jing. Data mining research based on business intelligence. Guizhou: Guizhou University, (2012).