Ensemble of surrogates-based optimization for identifying an optimal surfactant-enhanced aquifer remediation strategy at heterogeneous DNAPL-contaminated sites

Computers and Geosciences

Volumn 84, Issue , 2015, Pages 37-45

  Jiang, Xue ^a,b   Lu, Wenxi ^a,b   Hou, Zeyu ^a,b   Zhao, Haiqing ^c   Na, Jin ^a,b  

^a Jilin University   (China)

^b JILIN UNIVERSITY   (China)

^c SHENYANG INSTITUTE OF GEOLOGY AND MINERAL RESOURCES   (China)

Author keywords

DNAPL contamination; Ensemble surrogate; KELM; Optimization; Remediation strategy

Indexed keywords

AQUIFERS; CONSTRAINED OPTIMIZATION; CONTAMINATION; COST EFFECTIVENESS; GENETIC ALGORITHMS; HYDROGEOLOGY; LEARNING SYSTEMS; NEURAL NETWORKS; NITROBENZENE; NONLINEAR PROGRAMMING; OPTIMIZATION; POLLUTION; RADIAL BASIS FUNCTION NETWORKS; SURFACE ACTIVE AGENTS;

DENSE NON-AQUEOUS PHASE LIQUIDS; ENSEMBLE SURROGATE; KELM; NONLINEAR OPTIMIZATION MODEL; RADIAL BASIS FUNCTION ARTIFICIAL NEURAL NETWORKS; REMEDIATION STRATEGIES; SUPPORT VECTOR REGRESSION (SVR); SURFACTANT ENHANCED AQUIFER REMEDIATION;

GROUNDWATER POLLUTION;

AQUIFER POLLUTION; ENSEMBLE FORECASTING; ERROR ANALYSIS; NONAQUEOUS PHASE LIQUID; OPTIMIZATION; REMEDIATION; SURFACTANT;

EID: 84941565370     PISSN: 00983004     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cageo.2015.08.003     Document Type: Article

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