Research and application of automotive gears' grouping based on neural network techniques

Jing Sheng; Weizheng Yuan

Research and application of automotive gears' grouping based on neural network techniques

Jing Sheng, Weizheng Yuan

School of Mechanical Engineering

Northwestern Polytechnical University Xian

Research output: Contribution to journal › Article › peer-review

Abstract

For the gear grouping with a same processing route, neural network technology is used in the paper. First the parts are coded by analyzing their features. Then a neural network is implemented after learning and training. An intelligent mechanism of gear grouping is set up. As a result, the research provides a kind of new method for the technology design, technology equipment design and their management in enterprises.

Original language	English
Pages (from-to)	352-355
Number of pages	4
Journal	Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering)
Volume	31
Issue number	2
State	Published - Apr 2007

Keywords

Artificial neural network
Automotive gear
Part feature
Part grouping

Cite this

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title = "Research and application of automotive gears' grouping based on neural network techniques",

abstract = "For the gear grouping with a same processing route, neural network technology is used in the paper. First the parts are coded by analyzing their features. Then a neural network is implemented after learning and training. An intelligent mechanism of gear grouping is set up. As a result, the research provides a kind of new method for the technology design, technology equipment design and their management in enterprises.",

keywords = "Artificial neural network, Automotive gear, Part feature, Part grouping",

author = "Jing Sheng and Weizheng Yuan",

year = "2007",

month = apr,

language = "英语",

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pages = "352--355",

journal = "Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering)",

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Research and application of automotive gears' grouping based on neural network techniques. / Sheng, Jing; Yuan, Weizheng.
In: Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering), Vol. 31, No. 2, 04.2007, p. 352-355.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Research and application of automotive gears' grouping based on neural network techniques

AU - Sheng, Jing

AU - Yuan, Weizheng

PY - 2007/4

Y1 - 2007/4

N2 - For the gear grouping with a same processing route, neural network technology is used in the paper. First the parts are coded by analyzing their features. Then a neural network is implemented after learning and training. An intelligent mechanism of gear grouping is set up. As a result, the research provides a kind of new method for the technology design, technology equipment design and their management in enterprises.

AB - For the gear grouping with a same processing route, neural network technology is used in the paper. First the parts are coded by analyzing their features. Then a neural network is implemented after learning and training. An intelligent mechanism of gear grouping is set up. As a result, the research provides a kind of new method for the technology design, technology equipment design and their management in enterprises.

KW - Artificial neural network

KW - Automotive gear

KW - Part feature

KW - Part grouping

UR - https://www.scopus.com/pages/publications/34249989156

M3 - 文章

AN - SCOPUS:34249989156

SN - 1006-2823

VL - 31

SP - 352

EP - 355

JO - Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering)

JF - Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering)

IS - 2

ER -

Research and application of automotive gears' grouping based on neural network techniques

Abstract

Keywords

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