Study on the Optimal Parameters of Artificial Neural Networks by Applying Uniform Design

被引：0
|
作者：
Lin, Ta-Hsiang [1 ]
Chou, Jyh-Horng [1 ]
机构：
[1] Natl Kaohsiung Univ Appl Sci, Dept Elect Engn, Kaohsiung, Taiwan
来源：
2016 INTERNATIONAL CONFERENCE ON SYSTEM SCIENCE AND ENGINEERING (ICSSE) | 2016年
关键词：
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
When an artificial neural network (ANN) is used for modeling applications, the architecture and parameters of the network, like number of units and number of layers in each layer, need to be determined. In this paper, the uniform design is used to reduce the number of experiments to find the important factors, and the regression analysis methodology is then applied to find more accurate combination of design parameters for optimizing the ANN modeling.
引用
收藏
页数：2
相关论文
共 50 条
  • [31] Applying artificial vision techniques and artificial neural networks to autonomous quadcopter landing
    Robalino Ibarra, Luis Marcelo
    Segovia Freire, Alex Fabricio
    Rea Minango, Sylvia Nathaly
    del RocioVelasco Erazo, Nancy
    Chang, Oscar
    Mendoza Chipantasi, Dario Jose
    2017 IEEE SECOND ECUADOR TECHNICAL CHAPTERS MEETING (ETCM), 2017,
  • [32] Optimal section design of surface piercing propeller using artificial neural networks algorithm
    Zarezadeh, Masoud
    Nouri, Nowrouz Mohammad
    Madoliat, Reza
    Alagheband, Seyed Hamed Seyed
    SHIPS AND OFFSHORE STRUCTURES, 2024,
  • [33] Optimal design of plane frame structures using artificial neural networks and ratio variables
    Kao, Chin-Sheng
    Yeh, I-Cheng
    STRUCTURAL ENGINEERING AND MECHANICS, 2014, 52 (04) : 739 - 753
  • [34] Optimal experimental design and artificial neural networks applied to the photochemically enhanced Fenton reaction
    Göb, S
    Oliveros, E
    Bossmann, SH
    Braun, AM
    Nascimento, CAO
    Guardani, R
    WATER SCIENCE AND TECHNOLOGY, 2001, 44 (05) : 339 - 345
  • [35] The Implementation of Artificial Neural Networks Applying to Software Reliability Modeling
    Lo, Jung-Hua
    CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS, 2009, : 4349 - 4354
  • [36] Research of deflection data compensation by applying artificial neural networks
    Hu, S. R.
    Chen, W. M.
    Cai, X. X.
    Liang, Z. B.
    Zhang, P.
    STRUCTURAL HEALTH MONITORING AND INTELLIGENT INFRASTRUCTURE, VOLS 1 AND 2, 2006, : 755 - 758
  • [37] Applying artificial neural networks to bank-decision simulations
    Witkowska D.
    International Advances in Economic Research, 1999, 5 (3) : 350 - 368
  • [38] Use of artificial neural networks for predicting optimal alum doses and treated water quality parameters
    Maier, HR
    Morgan, N
    Chow, CWK
    ENVIRONMENTAL MODELLING & SOFTWARE, 2004, 19 (05) : 485 - 494
  • [39] Artificial Neural Networks Parameters Optimization with Design of Experiments: An Application in Ferromagnetic Materials Modeling
    Laosiritaworn, Wimalin
    Chotchaithanakorn, Nantakarn
    CHIANG MAI JOURNAL OF SCIENCE, 2009, 36 (01): : 83 - 91
  • [40] Estimation and Design of U-slot Physical Patch Parameters with Artificial Neural Networks
    Uzer, D.
    Gultekin, S. S.
    Dundar, O.
    PROCEEDINGS OF PROGRESS IN ELECTROMAGNETICS RESEARCH SYMPOSIUM (PIERS 2012), 2012, : 549 - 553
12345