The Optimum Method on Injection Molding Condition Based on RBF Network and Ant Colony Algorithm

被引：0
|
作者：
Huang, Fengli [1 ]
Gu, Jinmei [1 ]
Xu, Jinhong [1 ]
机构：
[1] Jiaxing Univ, Sch Mech & Elect Engn, Jiaxing, Zhejiang, Peoples R China
来源：
WORLD SUMMIT ON GENETIC AND EVOLUTIONARY COMPUTATION (GEC 09) | 2009年
关键词：
Plastic injection; molding condition; excellent degree; ant-colony algorithm; SYSTEM;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Aiming at the two principal; quality factors (warpage quantity and shrinkage rate) in injection molding process, the optimum method on injection molding condition based on RBF network and ant colony algorithm is provided. The definition and calculation method of excellent degree are given first and then the optimum method of the approximate model based on radial basis neural network is given. In the case study of plastic injection of fruit plate, the range of molding condition and the design method of design variables based on excellent degree are given, then the approximate model is gotten by Hyper-Latin square experiment and RBF network, the optimum result is gotten by improved ant colony algorithm of continuous field. It shows that the optimum result of plastic injection parameters based on radial basis neural network response surface and ant colony algorithm is reliable, and has good practical meaning.
引用
收藏
页码：835 / 838
页数：4
相关论文
共 50 条
  • [1] Optimization of Processing Parameters in Injection Molding Based on Adaptive Ant Colony Algorithm
    Huang, Fengli
    Chen, Shuisheng
    Gu, Jinmei
    [J]. MATERIALS SCIENCE AND ENGINEERING, PTS 1-2, 2011, 179-180 : 304 - +
  • [2] Forecasting GDP Growth Based on Ant Colony Clustering Algorithm and RBF Neural Network
    Zhao, Jianna
    Wang, Xinying
    Wu, Zhuozheng
    [J]. 2008 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6, 2008, : 1839 - 1843
  • [3] Application of RBF Neural Network Based on Ant Colony Algorithm in Credit Risk Evaluation of Construction Enterprises
    Wu Yunna
    Si Zhaomin
    [J]. 2008 INTERNATIONAL CONFERENCE ON RISK MANAGEMENT AND ENGINEERING MANAGEMENT, ICRMEM 2008, PROCEEDINGS, 2008, : 653 - 658
  • [4] Wireless sensor network routing method based on improved ant colony algorithm
    Zou, Zongfeng
    Qian, Ying
    [J]. JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2019, 10 (03) : 991 - 998
  • [5] A service discovery method based on referral network and ant-colony algorithm
    Xie X.-Q.
    Song C.-C.
    Zhang Z.-Q.
    [J]. Jisuanji Xuebao/Chinese Journal of Computers, 2010, 33 (11): : 2093 - 2103
  • [6] Wireless sensor network routing method based on improved ant colony algorithm
    Zongfeng Zou
    Ying Qian
    [J]. Journal of Ambient Intelligence and Humanized Computing, 2019, 10 : 991 - 998
  • [7] Ant colony algorithm for TSP based on hopfield network
    Yao, Wanye
    Zheng, Guiwen
    Li, Wei
    Wang, Zhengying
    [J]. DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 2006, 13E : 2928 - 2931
  • [8] Optimum route sequence search in SPN based on ant colony algorithm
    Huang, Guang-Qiu
    He, Xing
    Su, Hai-Yang
    [J]. Xitong Fangzhen Xuebao / Journal of System Simulation, 2008, 20 (17): : 4555 - 4559
  • [9] A method for power equipment condition monitoring and fault location based on improved ant colony algorithm
    Tong, Wei
    Huang, Qi-Ping
    [J]. International Journal of Energy Technology and Policy, 2024, 19 (3-4) : 363 - 376
  • [10] Node topology location method of SDN social network based on ant colony algorithm
    He, Lichun
    Li, Jing
    [J]. JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING, 2022, 22 (03) : 925 - 933
12345