Research on Application of Regression Least Squares Support Vector Machine on Performance Prediction of Hydraulic Excavator

Author

Chen, Zhan-bo

Source

Journal of Control Science and Engineering

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-4, 4 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-11-11

Country of Publication

Egypt

No. of Pages

4

Main Subjects

Electronic engineering
Information Technology and Computer Science

Abstract EN

In order to improve the performance prediction accuracy of hydraulic excavator, the regression least squares support vector machine is applied.

First, the mathematical model of the regression least squares support vector machine is studied, and then the algorithm of the regression least squares support vector machine is designed.

Finally, the performance prediction simulation of hydraulic excavator based on regression least squares support vector machine is carried out, and simulation results show that this method can predict the performance changing rules of hydraulic excavator correctly.

American Psychological Association (APA)

Chen, Zhan-bo. 2014. Research on Application of Regression Least Squares Support Vector Machine on Performance Prediction of Hydraulic Excavator. Journal of Control Science and Engineering،Vol. 2014, no. 2014, pp.1-4.
https://search.emarefa.net/detail/BIM-1040208

Modern Language Association (MLA)

Chen, Zhan-bo. Research on Application of Regression Least Squares Support Vector Machine on Performance Prediction of Hydraulic Excavator. Journal of Control Science and Engineering No. 2014 (2014), pp.1-4.
https://search.emarefa.net/detail/BIM-1040208

American Medical Association (AMA)

Chen, Zhan-bo. Research on Application of Regression Least Squares Support Vector Machine on Performance Prediction of Hydraulic Excavator. Journal of Control Science and Engineering. 2014. Vol. 2014, no. 2014, pp.1-4.
https://search.emarefa.net/detail/BIM-1040208

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1040208