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Design and implementation of a hybrid model based on two-layer decomposition method coupled with extreme learning machines to support real-time environmental monitoring of water quality parameters.
Fijani, Elham; Barzegar, Rahim; Deo, Ravinesh; Tziritis, Evangelos; Skordas, Konstantinos.
Affiliation
  • Fijani E; School of Geology, College of Science, University of Tehran, Tehran, Iran. Electronic address: efijani@ut.ac.ir.
  • Barzegar R; Department of Earth Sciences, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran; Department of Bioresource Engineering, McGill University, 21111 Lakeshore, Ste Anne de Bellevue, Quebec H9X3V9, Canada. Electronic address: rm.barzegar@tabrizu.ac.ir.
  • Deo R; School of Agricultural Computational and Environmental Sciences, International Centre for Applied Climate Sciences, Institute of Agriculture and Environment, University of Southern Queensland, Springfield, Australia. Electronic address: ravinesh.Deo@usq.edu.au.
  • Tziritis E; Hellenic Agricultural Organization, Soil and Water Resources Institute, 57400 Sindos, Greece. Electronic address: dir.lri@nagref.gr.
  • Skordas K; Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fitokou street, 38446 Volos, Greece. Electronic address: kskord@apae.uth.gr.
Sci Total Environ ; 648: 839-853, 2019 Jan 15.
Article in En | MEDLINE | ID: mdl-30138884
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Sci Total Environ Year: 2019 Document type: Article Country of publication: Netherlands
Fulltext
Add to My VHL
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Sci Total Environ Year: 2019 Document type: Article Country of publication: Netherlands