Identifying groundwater contaminant sources based on a KELM surrogate model together with four heuristic optimization algorithms-Reference-Cited by-同舟云学术

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Identifying groundwater contaminant sources based on a KELM surrogate model together with four heuristic optimization algorithms

Published:2020-04 Issue: Volume:138 Page:103540
ISSN:0309-1708
Container-title:Advances in Water Resources
language:en
Short-container-title:Advances in Water Resources

Author:

Zhao Ying,Qu Ruizhuo,Xing Zhenxiang,Lu Wenxi

Funder

National Natural Science Foundation of China

National Key R&D Program of China

Postdoctoral Science Foundation of China

Postdoctoral Science Foundation

Natural Science Foundation of Heilongjiang Province

Northeast Agricultural University

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference43 articles.

1. A linked simulation-optimization model for solving the unknown groundwater pollution source identification problems [J];Ayvaz;J. Contam. Hydrol.,2010

2. The computer as a physical system: a microscopic quantum mechanical hamiltonian model of computers as represented by Turing machines [J];Benioff;J. Stat. Phys.,1980

3. Spectral-Spatial classification of hyperspectral image based on Kernel extreme learning machine [J];Chen;Remote Sens.,2014

4. Identification of unknown groundwater pollution sources using classical optimization with linked simulation [J];Datta;J. Hydro-Environ. Res.,2011

5. Recent advances in surrogate-based optimization [J];Forrester;Prog. Aerosp. Sci.,2009

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