Acta Optica Sinica, Volume. 42, Issue 2, 0229001(2022)

Particle Size Distribution Inversion of Cuckoo Search Algorithm Using Weber Distribution

Liang Shan1, Tingting Zha1, Ming Kong2、*, and Bo Hong1
Author Affiliations
  • 1Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, Hangzhou, Zhejiang 310018, China
  • 2College of Metrology & Measurement Engineering, China Jiliang University, Hangzhou, Zhejiang 310018, China;
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    Figures & Tables(12)
    Search process of WCS algorithm
    Relative root mean square error curves of unimodal particle size distribution inversion by different algorithms
    Relative root mean square error curves of bimodal particle size distribution inversion by different algorithms
    Experimental setup for small angle forward scattering
    Scattering image of particle. (a) Particle background; (b) unimodal particle; (c) bimodal particle
    Experimental results of unimodal particle on Rosin-Rammlar distribution function inversion by WCS algorithm
    Experimental results of bimodal particle on Rosin-Rammlar distribution function inversion by WCS algorithm
    • Table 1. Parameter setting of small angle forward scattering system

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      Table 1. Parameter setting of small angle forward scattering system

      Particle size range /μmIncident light wavelength /nmLens focal length /mmRelative refractive index
      3.85--101.85632.8025.00(1.596-0.1i)/1.33
    • Table 2. Inversion results of different algorithms under unimodal distribution

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      Table 2. Inversion results of different algorithms under unimodal distribution

      AlgorithmEvaluation criteriaParameterJohnson’s SBRosin-RammlerNormal
      Mean valuedM /μm10.00045.00010.00045.00010.00045.000
      AFSAStandard deviationd /10-4M /(10-4 μm)4.5500.5303.7202.4803.1004.440
      RRMSE /(10-4 μm)0.42015.0009.180
      Mean valuedM /μm10.00045.00010.00045.00010.00045.000
      ABCStandard deviationd /10-6M /(10-6 μm)2000.0001000.0000.0940.0666.6306.280
      RRMSE /(10-6 μm)20000.0000.0352.260
      Mean valuedM /μm10.00045.00010.00045.00010.00045.000
      CSStandard deviationd /10-11M /(10-12 μm)1.6002.4101.2408.1700.5205.880
      RRMSE /(10-11 μm)3.3903.3901.010
      Mean valuedM /μm10.00045.00010.00045.00010.00045.000
      CCSStandard deviationd /10-13M /(10-13 μm)0.9000.1009.8803.2906.5205.860
      RRMSE /(10-13 μm)3.0908.3708.460
      Mean valuedM /μm10.00045.00010.00045.00010.00045.000
      PCSStandard deviationd /10-13M /(10-12 μm)1.6800.0104.2100.3309.0201.620
      RRMSE /(10-13 μm)3.8708.9508.740
      Mean valuedM /μm10.00045.00010.00045.00010.00045.000
      MCSStandard deviationd /10-12M /(10-12 μm)0.1600.0301.1100.5401.9302.040
      RRMSE /(10-13 μm)5.17025.10019.400
      Mean valuedM /μm10.00045.00010.00045.00010.00045.000
      WCSStandard deviationd /10-13M /(10-14 μm)1.0800.6300.2100.9900.3102.360
      RRMSE /(10-14 μm)6.6808.5206.570
    • Table 3. Inversion results of different algorithms under bimodal distribution

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      Table 3. Inversion results of different algorithms under bimodal distribution

      AlgorithmEvaluation criteriaParameterJohnson’s SBRosin-RammlerNormal
      Mean valued1d2M1 /μmM2 /μm6.00005.990030.000070.00005.99006.000030.000070.00005.99006.000030.000069.9900
      AFSAStandard deviationd1 /10-4d2 /10-4M1 /(10-4 μm)M2 /(10-4 μm)32.0000 5.20006.71001.14009.94002.410036.0000 3.390023.0000 2.080018.0000 2.4500
      RRMSE /μm0.00720.00220.0035
      Mean valued1d2M1 /μmM2 /μm5.99006.160030.010070.03005.99006.020030.010070.10006.00006.040030.000070.0300
      ABCStandard deviationd1d2M1 /μmM2 /μm0.0380 0.31200.02400.07600.03400.01900.0250 0.19700.00200.00100.0010 0.0020
      RRMSE /μm1.58000.33000.4800
      Mean valued1d2M1 /μmM2 /μm6.00006.000030.000070.00006.00006.000030.000070.00006.00006.000030.000070.0000
      CSStandard deviationd1 /10-4d2 /10-4M1 /(10-5 μm)M2 /(10-4 μm)5.7400 6.61004.2400 2.30002.7000 1.32008.5900 6.82003.1800 2.81007.55003.4800
      RRMSE /μm0.00210.00160.0011
      Mean valued1d2M1 /μmM2 /μm6.00006.000030.000070.00006.00006.000030.000070.00006.00006.000030.000070.0000
      CCSStandard deviationd1 /10-6d2 /10-6M1 /(10-6 μm)M2 /(10-6 μm)4.48001.47000.0980.61000.50000.97000.5100 2.68004.61003.21003.36008.1700
      RRMSE /(10-5 μm)0.40000.31002.0400
      Mean valued1d2M1 /μmM2 /μm6.00006.000030.000070.00006.00006.000030.000070.00006.00006.000030.000070.0000
      PCSStandard deviationd1 /10-6d2 /10-6M1 /(10-6 μm)M2 /(10-6 μm)0.28000.7000 0.21001.30003.38002.0000 6.290031.30001.06004.32000.57002.8300
      RRMSE /(10-5 μm)0.47002.88000.7800
      Mean valued1d2M1 /μmM2 /μm6.00006.000030.000070.00006.00006.000030.000070.00006.00006.000030.000070.0000
      MCSStandard deviationd1 /10-6d2 /10-6M1 /(10-6 μm)M2 /(10-6 μm)5.590015.60000.45004.38005.47007.39004.4300 44.40001.88001.76000.39001.3900
      RRMSE /(10-5 μm)0.84003.83000.6400
      Mean valued1d2M1 /μmM2 /μm6.00006.000030.000070.00006.00006.000030.000070.00006.00006.000030.000070.0000
      WCSStandard deviationd1 /10-7d2 /10-6M1 /(10-8 μm)M2 /(10-7 μm)3.64000.4800 6.76001.35001.49000.12006.27005.11005.13001.24007.87008.3100
      RRMSE /(10-6 μm)1.05000.82003.4900
    • Table 4. Results of unimodal particle swarm inversion by CS algorithm and WCS algorithm

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      Table 4. Results of unimodal particle swarm inversion by CS algorithm and WCS algorithm

      AlgorithmDistributionfunctionM /μmRelativeerror /%
      Johnson’s SB50.080.16
      CSRosin-Rammler48.163.67
      Normal50.100.21
      Johnson’s SB50.050.10
      WCSRosin-Rammler48.263.48
      Normal50.040.08
    • Table 5. Results of bimodal particle swarm inversion by CS algorithm and WCS algorithm

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      Table 5. Results of bimodal particle swarm inversion by CS algorithm and WCS algorithm

      AlgorithmDistribution functionM1 /μmM2 /μmRelative errorof M1 /%Relative errorof M2 /%
      Johnson’s SB50.24101.720.481.72
      CSRosin-Rammler50.03100.070.060.07
      Normal50.11101.650.221.65
      Johnson’s SB50.13101.550.261.55
      WCSRosin-Rammler50.01100.010.020.01
      Normal50.05101.490.101.49
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    Liang Shan, Tingting Zha, Ming Kong, Bo Hong. Particle Size Distribution Inversion of Cuckoo Search Algorithm Using Weber Distribution[J]. Acta Optica Sinica, 2022, 42(2): 0229001

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    Paper Information

    Category: Scattering

    Received: Jul. 5, 2021

    Accepted: Aug. 13, 2021

    Published Online: Dec. 29, 2021

    The Author Email: Kong Ming (mkong@cjlu.edu.cn)

    DOI:10.3788/AOS202242.0229001

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