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Prediction of Wheel Wear Data Based on GA-SVM

DOI: 10.12677/HJDM.2024.141003, PP. 20-25

Keywords: 车轮磨耗,支持向量机,遗传算法,大数据技术
Wheel Wear
, Support Vector Machine, Genetic Algorithm, Big Data Technology

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During the operation of train vehicles, train wheels play an important role in supporting the weight of the entire train and ensuring train safety. Therefore, research on predicting wheel wear has be-come extremely important. With the continuous development of big data analysis technology, various intelligent algorithms are gradually being introduced into the prediction of wheel wear to im-prove the accuracy of prediction. In this context, this study uses genetic algorithms and support vector machine models for regression prediction of wheel wear. The RMSE value of the predicted result is only 0.059, indicating that the model has excellent predictive performance.


[1]  Pombo, J., Ambrósio, J., Pereira, M., et al. (2011) Development of a Wear Prediction Tool for Steel Railway Wheels Using Three Alternative Wear Functions. Wear, 271, 238-245.
[2]  Vapnik, V.N. (1995) The Nature of Statistical Learning Theory. Springer-Verlag, NY, USA.
[3]  Goldberg, D.E. and Holland, J.H. (1988) Genetic Algorithms and Machine Learning. Machine Learning, 3, 95-99.
[4]  Cho, J.H., Kim, J.S., Lim, J.S., et al. (2006) Optimal Acoustic Search Path Planning Based on Genetic Algorithm in Discrete Path System. OCEANS 2006 - Asia Pacific, Singapore, 16-19 May 2006, 1-5.
[5]  Hsu, C.-W., Chang, C.-C. and Lin, C.-J. (2004) A Prac-tical Guide to Support Vector Classification. Technical Report, Department of Computer Science and Information Engi-neering, National Taiwan University.
[6]  Tassini, N., Quost, X., Lewis, R., et al. (2008) A Nu-merical Model of Twin Disc Test Arrangement for Evaluating Railway Wheel Wear Prediction Algorithms. International Joint Tribology Conference, Vol. 43369, 469-471.
[7]  Katoch, S., Chauhan, S.S. and Kumar, V. (2021) A Review on Genetic Algorithm: Past, Present, and Future. Multimedia Tools and Applications, 80, 8091-8126.
[8]  Sivanandam, S.N. and Deepa, S.N. (2008) Introduction to Ge-netic Algorithm. 1st Edition, Springer-Verlag, Berlin Heidelberg.
[9]  Jebari, K. (2013) Selection Methods for Genetic Algorithms. Abdelmalek Essaadi University. International Journal of Emerging Sciences, 3, 333-344.
[10]  Pearce, T.G. and Sherratt, N.D. (1991) Prediction of Wheel Profile Wear. Wear, 144, 343-351.


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