Laser & Optoelectronics Progress, Volume. 57, Issue 21, 212001(2020)

Classification of Electroencephalography Based on BP Neural Network Optimized By Crossover Operation of Artificial Bee Colonies

Xu Jian, Chen Qianqian*, and Liu Xiuping
Author Affiliations
  • 西安工程大学电子信息学院, 陕西 西安 710048
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    Figures & Tables(12)
    Different kinds of individuals. (a) P1; (b) P2
    Schematic of crossover operation
    Topological structure of three-layer BP neural network
    Improved global ABC to optimize process of BP neural network
    Average fitness curves of three kinds of neural networks
    Prediction error curves of two networks
    Training errors of three kinds of neural networks
    Comparison of accuracy between CGABC-BP and other classification methods
    • Table 1. Standard test functions

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      Table 1. Standard test functions

      TrialfunctionFunctionnameFunction expressionSearch scopeOptimalvalue
      Griewankf5(r)=14000i=1Qri2-i=1Qcosri i +1[-10,10]f5(0)=0
      Rastriginf2(r)=i=1Q[ri2-10cos(2πri)+10][-5.12,5.12]f2(0)=0
      Spheref1(r)=i=1Qri2[-5.12,5.12]f1(0)=0
      Rosenbrockf6(r)=i=1Q-1[100(ri+1-ri2)2+(ri-1)2][-2.048,2.048]f6(0)=0
    • Table 2. Performance comparison of three algorithms

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      Table 2. Performance comparison of three algorithms

      Trial functionMethodOptimal valueConvergence rate /sMeanStandard value
      SABC3.83×10-5900.93.88×10-31.04×10-16
      GABC0230.08.30×10-131.41×10-17
      CGABC0191.45.47×10-160
      SABC0122.102.23×10-14
      GABC023.200
      CGABC015.200
      SABC1.05×10-1528.75.20×10-159.38×10-17
      GABC3.10×10-1817.28.03×10-135.08×10-17
      CGABC9.43×10-1814.34.31×10-182.66×10-17
      SABC3.10×10-15752.34.20×10-150.98
      GABC9.10×10-1622.35.45×10-150.61
      CGABC1.03×10-1819.18.76×10-170.11
    • Table 3. Training results of different BP neural networks

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      Table 3. Training results of different BP neural networks

      Neural networkMax iterationsMin interationsAverage interationsTarget error
      BP134657732964110-4
      GABC-BP32116421510-4
      CGABC-BP2146117510-4
    • Table 4. Accuracy results of feature classification of different BP neural networks unit:%

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      Table 4. Accuracy results of feature classification of different BP neural networks unit:%

      Neural networkP1P2P3P4P5P6P7Average accuracy
      BP81.284.583.785.782.483.282.983.4
      GABC-BP86.385.488.187.386.887.484.786.6
      CGABC-BP90.789.593.992.091.190.692.591.5
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    Xu Jian, Chen Qianqian, Liu Xiuping. Classification of Electroencephalography Based on BP Neural Network Optimized By Crossover Operation of Artificial Bee Colonies[J]. Laser & Optoelectronics Progress, 2020, 57(21): 212001

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    Paper Information

    Category: Optics in Computing

    Received: Dec. 17, 2019

    Accepted: --

    Published Online: Nov. 4, 2020

    The Author Email: Qianqian Chen (645615742@qq.com)

    DOI:10.3788/LOP57.212001

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