Optimal Selection of Multiple Parameters in Filling Processof Pressure Die Casting

doi:10.7523/j.issn.2095-6134.2004.4.016

Welcome to Journal of University of Chinese Academy of Sciences，Today is

Email Alert RSS 中文

›› 2004, Vol. 21 ›› Issue (4): 532-537.DOI: 10.7523/j.issn.2095-6134.2004.4.016

Previous Articles Next Articles

Optimal Selection of Multiple Parameters in Filling Processof Pressure Die Casting

GUI Gang^1,2, YU Jun^1,2, SU Li-Jie^1,2, NIE Yi-Yong¹

1. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China;
2. Graduate School, Chinese Academy of Sciences, Beijing 100039, China

Received:2003-06-27 Revised:2003-10-15 Online:2004-07-10

Abstract

Abstract:

A technological parameter optimal model with multi-object and multi-parameter is given. Some numericalsimulation results are firstly obtained by ProCAST when the technological parameters are specified. Then thesesimulation data are provided for the multi-layer feed-forward network training. As a result,the function,between theinput and output parameters,can be constructed by neural networks. Finally,the optimal problem may be solved byGenetic Algorithm. The most proper cast parameters are obtained.

Key words: die cast, neural network, genetic algorithm, interpolation

CLC Number:

TG249

GUI Gang, YU Jun, SU Li-Jie, NIE Yi-Yong. Optimal Selection of Multiple Parameters in Filling Processof Pressure Die Casting[J]. , 2004, 21(4): 532-537.

[1]	YU Wenxin, LI Kai, ZHOU Mingtuo, LI Jian, YANG Yang. Adaptive neural network for 3D channel amplitude prediction [J]. Journal of University of Chinese Academy of Sciences, 2021, 38(5): 678-686.
[2]	QIAN Huan, XIE Zhuochen, LIANG Xuwen. Single-event upsets fault tolerance of convolutional neural networks based on dropout algorithm [J]. Journal of University of Chinese Academy of Sciences, 2021, 38(5): 712-719.
[3]	JI Yufeng, ZHENG Min, TAN Chong, LIU Hong. Combination algorithm of spectrum sensing in vehicle network based on neural network [J]. Journal of University of Chinese Academy of Sciences, 2021, 38(4): 549-556.
[4]	HU Lina, GAO Shenghua. Hierarchical label-guided human parsing [J]. , 2020, 37(6): 820-827.
[5]	FENG Qixin, YANG Liao, WANG Weisheng, CHEN Tao, HUANG Shuangyan. CNN remote sensing crop classification based on time series spectral reconstruction [J]. , 2020, 37(5): 619-628.
[6]	WANG Hong, XU Youyu, TAN Chong, LIU Hong, ZHENG Min. Information fusion algorithm based on improved particle swarm BP neural network in WSN [J]. , 2020, 37(5): 673-680.
[7]	TANG Siqi, HAN Congying, GUO Tiande. Point matching algorithm based on machine learning method [J]. , 2020, 37(4): 450-457.
[8]	MING Weipeng, MA Guangbin, ZHANG Wenyi. Multi-satellite imaging task planning algorithms based on gene expression programming [J]. , 2020, 37(4): 532-538.
[9]	SUN Mingkun, LIANG Lingy, WANG Han, HE Wei, ZHAO Luyang. Facial landmark detection based on cascade convolutional neural network [J]. , 2020, 37(4): 562-569.
[10]	XUE Jianwei, TANG Liang, BU Zhiyong. Cooperative spectrum sensing based on neural network in cognitive radio [J]. , 2020, 37(3): 379-386.
[11]	SONG Han, YANG Weitun, GENG Xiurui, ZHAO Yongchao. Hyperspectral image classification based on convolutional neural network and active learning algorithm [J]. , 2020, 37(2): 169-176.
[12]	WANG Huijun, ZHAO Guiping, LI Liang, ZHANG Wei, QI Rong, LIU Jun. TOC prediction model for muddy source rocks based on convolutional neural network (CNN): a case study of the Hangjinqi area of the Ordos Basin [J]. , 2020, 37(1): 103-112.
[13]	SONG Xuming, SHEN Yifei, SHI Yuanming. Intelligent mobile edge network caching based on deep learning [J]. , 2020, 37(1): 128-135.
[14]	LI Kuangyu, ZHOU Mei, CHEN Jiuying, PAN Miaomiao, LI Chuanrong, TANG Lingli. An approach of improved gradient plus inverse distance squared for spatial interpolation of temperature [J]. , 2019, 36(4): 491-497.
[15]	WANG Jianfei, ZHANG Weiqiang, LIU Jia. Scene-independent sound event detection based on multi-state transition model [J]. , 2019, 36(2): 218-225.

Optimal Selection of Multiple Parameters in Filling Processof Pressure Die Casting

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments