• Acta Optica Sinica
  • Vol. 40, Issue 10, 1030002 (2020)
Ying Chen1、*, Can Zhang1, Chunyan Xiao2, Xueliang Zhao1、3, Yanxin Shi3, Hui Yang1, Zhengying Liu1, and Shaohua Li4
Author Affiliations
  • 1Hebei Province Key Laboratory of Test/Measurement Technology and Instrument, School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 0 66004, China
  • 2Institute of Resources & Environment, Henan Polytechnic University, Jiaozuo, Henan 454000, China;
  • 3Center for Hydrogeology and Environmental Geology, China Geological Survey, Baoding, Hebei 0 71051, China
  • 4Hebei Sailhero Environmental Protection High-tech Co., Ltd., Shijiazhuang, Hebei 0 50035, China
  • show less
    DOI: 10.3788/AOS202040.1030002 Cite this Article Set citation alerts
    Ying Chen, Can Zhang, Chunyan Xiao, Xueliang Zhao, Yanxin Shi, Hui Yang, Zhengying Liu, Shaohua Li. Study on Prediction Model of Soil Cadmium Content Moisture Content Correction Based on GWO-SVR[J]. Acta Optica Sinica, 2020, 40(10): 1030002 Copy Citation Text show less
    References

    [1] Wang S F, Han P, Wang J H et al. Application of X-ray fluorescence spectrometry on the detection of heavy metals in soil[J]. Journal of Food Safety & Quality, 7, 4394-4400(2016).

    [2] Cheng X, Zhou M M. Application progress of X-ray fluorescence spectroscopy in the detection of heavy metals in soil[J]. China Resources Comprehensive Utilization, 36, 98-100(2018).

    [3] Li Y L, Jin H Y, Wang D D et al. Study on proficiency testing of determination cadmium residues in honeysuckle[J]. Chinese Pharmaceutical Affairs, 33, 568-574(2019).

    [4] Jiang X. A comparative study on the determination of heavy metals in soil samples by PXRF, XRF, AAS and ICP-AES[J]. Pollution Control Technology, 32, 30-34(2019).

    [5] Wu X L. Study on X-ray fluorescence analysis technology of soil heavy metal element content[D]. Chengdu: Chengdu University of Technology(2016).

    [6] Wang S F, Luo N, Han P. Application of energy-dispersive X-ray fluorescence spectrometry to the determination of As, Zn, Pb and Cr in soil[J]. Spectroscopy and Spectral Analysis, 38, 1648-1654(2018).

    [7] Ren D, Shen J, Ren S et al. An X-ray fluorescence spectroscopy pretreatment method for detection of heavy metal content in soil[J]. Spectroscopy and Spectral Analysis, 38, 3934-3940(2018).

    [8] Fan J N, Zhang Y, He X M et al. BP neural network based prediction and evaluation of heavy metal pollution in soil around the enterprises in key areas of Hubei province[J]. Journal of Huazhong Agricultural University, 38, 55-62(2019).

    [9] Wan M X, Qu M K, Hu W Y et al. Estimation of soil pH using PXRF spectrometry and Vis-NIR spectroscopy for rapid environmental risk assessment of soil heavy metals[J]. Process Safety and Environmental Protection, 132, 73-81(2019).

    [10] Qu M K, Chen J, Li W D et al. Correction of in-situ portable X-ray fluorescence (PXRF) data of soil heavy metal for enhancing spatial prediction[J]. Environmental Pollution, 254, 112993(2019).

    [11] Nawar S, Delbecque N, Declercq Y et al. Can spectral analyses improve measurement of key soil fertility parameters with X-ray fluorescence spectrometry?[J]. Geoderma, 350, 29-39(2019).

    [12] Gu Y L, Liu X F, Yang X et al. Soil moisture distribution characteristics and variation characteristics in Hebei province[J]. Journal of Arid Land Resources and Environment, 25, 118-121(2011).

    [13] Liang J H, Liu P P, Chen Z et al. Rapid evaluation of arsenic contamination in paddy soils using field portable X-ray fluorescence spectrometry[J]. Journal of Environmental Sciences, 64, 345-351(2018).

    [14] Ravansari R, Lemke L D. Portable X-ray fluorescence trace metal measurement in organic rich soils: pXRF response as a function of organic matter fraction[J]. Geoderma, 319, 175-184(2018).

    [15] Silva E A, Weindorf D C. Silva S H G, et al. Advances in tropical soil characterization via portable X-ray fluorescence spectrometry[J]. Pedosphere, 29, 468-482(2019).

    [16] Zhu S L, Qiu X L, Yin Y R et al. Two-step-hybrid model based on data preprocessing and intelligent optimization algorithms (CS and GWO) for NO2 and SO2 forecasting[J]. Atmospheric Pollution Research, 10, 1326-1335(2019).

    [17] Maroufpoor S, Maroufpoor E, Bozorg-Haddad O et al. Soil moisture simulation using hybrid artificial intelligent model: hybridization of adaptive neuro fuzzy inference system with grey wolf optimizer algorithm[J]. Journal of Hydrology, 575, 544-556(2019).

    [18] Wu J R, Cui Z S, Chen Y Y et al. A new hybrid model to predict the electrical load in five states of Australia[J]. Energy, 166, 598-609(2019).

    [19] Wei Z L, Zhao H, Han B J et al. Grey wolf optimization algorithm with self-adaptive searching strategy[J]. Computer Science, 44, 259-263(2017).

    [20] Oudira H, Gouri A, Mezache A. Optimization of distributed CFAR detection using grey wolf algorithm[J]. Procedia Computer Science, 158, 74-83(2019).

    Ying Chen, Can Zhang, Chunyan Xiao, Xueliang Zhao, Yanxin Shi, Hui Yang, Zhengying Liu, Shaohua Li. Study on Prediction Model of Soil Cadmium Content Moisture Content Correction Based on GWO-SVR[J]. Acta Optica Sinica, 2020, 40(10): 1030002
    Download Citation