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Soil Heavy Metal Content Prediction Based on a Deep Belief Network and Random Forest Model.
Chen, Ying; Liu, Zhengying; Zhao, Xueliang; Sun, Shicheng; Li, Xiao; Xu, Chongxuan.
Afiliação
  • Chen Y; Hebei Province Key Laboratory of Test/Measurement Technology and Instrument, School of Electrical Engineering, 530247Yanshan University, Qinhuangdao, China.
  • Liu Z; Hebei Province Key Laboratory of Test/Measurement Technology and Instrument, School of Electrical Engineering, 530247Yanshan University, Qinhuangdao, China.
  • Zhao X; Hebei Province Key Laboratory of Test/Measurement Technology and Instrument, School of Electrical Engineering, 530247Yanshan University, Qinhuangdao, China.
  • Sun S; Center for Hydrogeology and Environmental Geology, China Geological Survey, Geological Environment Monitoring Engineering Technology Innovation Center of The Ministry of Natural Resources, Baoding, China.
  • Li X; Hebei Province Key Laboratory of Test/Measurement Technology and Instrument, School of Electrical Engineering, 530247Yanshan University, Qinhuangdao, China.
  • Xu C; Hebei Province Key Laboratory of Test/Measurement Technology and Instrument, School of Electrical Engineering, 530247Yanshan University, Qinhuangdao, China.
Appl Spectrosc ; 76(9): 1068-1079, 2022 Sep.
Article em En | MEDLINE | ID: mdl-35583031

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Solo / Metais Pesados Tipo de estudo: Clinical_trials / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Appl Spectrosc Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Solo / Metais Pesados Tipo de estudo: Clinical_trials / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Appl Spectrosc Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China País de publicação: Estados Unidos