Application of AF-SVM based on the Structure of the Machine

Shengran Meng, Shaohui Su, Lu Lu, Dongyang Zhang, Chang Chen, Guojin Chen

Abstract

The problem of time-consuming in optimization of large complex structures such as grinder, The method of selecting support vector machine parameters based on artificial fish-swarm algorithm and its application, The feasibility of replacing time-consuming finite element analysis for structural optimization is validated. Based on the plane grinder bed, the orthogonal experimental design method was used to select the sample points in the structure parameter space of the grinder bed; The sample point is simulated by ANSYS, and the sample set is produced; By using the better parallelism and the strong global optimization ability of artificial fish swarm algorithm, the optimal parameter combination of SVM is obtained, and the approximate modeling of the grinder bed model is completed. The results show that compared with the traditional finite element method, the method not only significantly improves the computation efficiency, but also has good accuracy.

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Paper Citation


in Harvard Style

Meng S., Su S., Lu L., Zhang D., Chen C. and Chen G. (2018). Application of AF-SVM based on the Structure of the Machine.In Proceedings of the 2nd International Conference on Intelligent Manufacturing and Materials - Volume 1: ICIMM, ISBN 978-989-758-345-2, pages 304-310. DOI: 10.5220/0007531003040310


in Bibtex Style

@conference{icimm18,
author={Shengran Meng and Shaohui Su and Lu Lu and Dongyang Zhang and Chang Chen and Guojin Chen},
title={Application of AF-SVM based on the Structure of the Machine},
booktitle={Proceedings of the 2nd International Conference on Intelligent Manufacturing and Materials - Volume 1: ICIMM,},
year={2018},
pages={304-310},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007531003040310},
isbn={978-989-758-345-2},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Intelligent Manufacturing and Materials - Volume 1: ICIMM,
TI - Application of AF-SVM based on the Structure of the Machine
SN - 978-989-758-345-2
AU - Meng S.
AU - Su S.
AU - Lu L.
AU - Zhang D.
AU - Chen C.
AU - Chen G.
PY - 2018
SP - 304
EP - 310
DO - 10.5220/0007531003040310