Selection of Initial Weights and Thresholds Based on the Genetic Algorithm with the Optimized Back-Propagation Neural Network

被引：0
|
作者：
Yi, Xiaodong [1 ]
机构：
[1] Dalian Univ Technol, Lab Surveying & Spatial Informat Technol, Sch Civil Engn, Dalian, Peoples R China
来源：
2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) | 2015年
关键词：
BP neural networks; genetic algorithms; initial weight; network errors; optimization; STRUCTURAL DAMAGE DETECTION; CANTILEVER;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The Genetic Algorithm (GA) has been used for artificial neural network optimization of initial weights and thresholds matrix. The initial weights and thresholds which has been optimized is equivalent to set up a reference range for artificial neural network to search optimization, therefore the performance of improved artificial neural network could be enhanced. Matlab2010 has been used as a platform for experiments. With the actual case, the error between the algorithm of individual using the BP (Back-Propagation) network and the optimized GA-BP (Genetic Algorithm and Back-Propagation) neural network with the genetic algorithm has been carefully analyzed. Results show that all indicators improved for the latter.
引用
收藏
页码：173 / 177
页数：5
相关论文
共 50 条
  • [1] Identification of Baijiu based on the Raman spectroscopy and back-propagation neural network optimized using genetic algorithm
    Zong, Xuyan
    Zhou, Xianjiang
    Wen, Lei
    Gan, Shuang
    Li, Li
    [J]. JOURNAL OF FOOD COMPOSITION AND ANALYSIS, 2024, 126
  • [2] A wildfire occurrence risk model based on a back-propagation neural network-optimized genetic algorithm
    Zhang, Hao
    Liu, Hui
    Ma, Guoqing
    Zhang, Yang
    Yao, Jinxia
    Gu, Chao
    [J]. FRONTIERS IN ENERGY RESEARCH, 2023, 10
  • [3] A New Back-Propagation Neural Network Optimized with Cuckoo Search Algorithm
    Nawi, Nazri Mohd
    Khan, Abdullah
    Rehman, Mohammad Zubair
    [J]. COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, PT I, 2013, 7971 : 413 - 426
  • [4] A new back-propagation neural network optimized with cuckoo search algorithm
    Nawi, Nazri Mohd
    Khan, Abdullah
    Rehman, Mohammad Zubair
    [J]. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, 7971 : 413 - 426
  • [5] A predictive model for chinese children with developmental dyslexia-Based on a genetic algorithm optimized back-propagation neural network
    Wang, Runzhou
    Bi, Hong-Yan
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2022, 187
  • [6] An Optimized Method for Electric Power System Harmonic Measurement Based on Back-propagation Neural Network and Modified Genetic Algorithm
    Li, Tao
    Chen, Yuan-rui
    Li, Guang-ming
    [J]. 2009 3RD INTERNATIONAL CONFERENCE ON POWER ELECTRONICS SYSTEMS AND APPLICATIONS: ELECTRIC VEHICLE AND GREEN ENERGY, 2009, : 87 - 87
  • [7] Gravity anomaly interpolation based on Genetic Algorithm improved Back-Propagation Neural Network
    Zhao Dongming
    Bao Huan
    Wang Qingbin
    Gao Zhan
    [J]. SEVENTH INTERNATIONAL SYMPOSIUM ON PRECISION ENGINEERING MEASUREMENTS AND INSTRUMENTATION, 2011, 8321
  • [8] Transformer Fault Diagnosis Based on Back-Propagation Neural Network Optimized by Cuckoo Search Algorithm
    Wang, Yan
    Zhang, Liguo
    [J]. CONFERENCE PROCEEDINGS OF 2017 3RD IEEE INTERNATIONAL CONFERENCE ON CONTROL SCIENCE AND SYSTEMS ENGINEERING (ICCSSE), 2017, : 383 - 386
  • [9] An Improved Back-Propagation Neural Network Algorithm
    Hao, Pan
    [J]. MECHATRONICS ENGINEERING, COMPUTING AND INFORMATION TECHNOLOGY, 2014, 556-562 : 4586 - 4590
  • [10] An Investigation of Back-propagation Neural Network on University Selection
    Maharani, Sitti Syarah
    Yaakob, Razali
    Udzir, Nur Izura
    [J]. 2015 2ND INTERNATIONAL CONFERENCE ON COMPUTER, COMMUNICATIONS, AND CONTROL TECHNOLOGY (I4CT), 2015,
12345