A comparative research of different ensemble surrogate models based on set pair analysis for the DNAPL-contaminated aquifer remediation strategy optimization

Journal of Contaminant Hydrology

Volumn 203, Issue , 2017, Pages 28-37

  Hou, Zeyu ^a,b   Lu, Wenxi ^a,b   Xue, Haibo ^c   Lin, Jin ^d  

^a Jilin University   (China)

^b JILIN UNIVERSITY   (China)

^c Liaoning Chaihe Reservoir Administration   (China)

^d NANJING HYDRAULIC RESEARCH INSTITUTE   (China)

Author keywords

DNAPLs; Ensemble surrogate model; Set pair analysis; Simulation optimization

Indexed keywords

AQUIFERS; GROUNDWATER POLLUTION; INTERPOLATION; NEURAL NETWORKS; OPTIMIZATION; POLLUTION; RADIAL BASIS FUNCTION NETWORKS;

DNAPLS; RADIAL BASIS FUNCTION ARTIFICIAL NEURAL NETWORKS; REMEDIATION STRATEGIES; SET PAIR ANALYSIS; SIMULATION OPTIMIZATION; SUPPORT VECTOR REGRESSION (SVR); SURFACTANT ENHANCED AQUIFER REMEDIATION; SURROGATE MODEL;

FUEL ADDITIVES;

AQUIFER POLLUTION; COMPARATIVE STUDY; ENSEMBLE FORECASTING; OPTIMIZATION; REMEDIATION; SIMULATION; SURFACTANT;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOREMEDIATION; CONTROLLED STUDY; DENSE NONAQUEOUS PHASE LIQUID; ENSEMBLE SURROGATE MODEL; INTERMETHOD COMPARISON; KRIGING; METHODOLOGY; MODEL; NONAQUEOUS PHASE LIQUID; PRIORITY JOURNAL; PROCESS OPTIMIZATION; RADIAL BASIS FUNCTION ARTIFICIAL NEURAL NETWORK; SET PAIR ANALYSIS; SIMULATION; SUPPORT VECTOR MACHINE; SURFACTANT ENHANCED AQUIFER REMEDIATION; ANALYSIS; COMPARATIVE STUDY; ECOSYSTEM RESTORATION; HYDROLOGY; PROCEDURES; THEORETICAL MODEL; WATER POLLUTANT;

GROUND WATER; NITROBENZENE; NITROBENZENE DERIVATIVE; SURFACTANT; WATER POLLUTANT;

ENVIRONMENTAL RESTORATION AND REMEDIATION; GROUNDWATER; HYDROLOGY; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); NITROBENZENES; SURFACE-ACTIVE AGENTS; WATER POLLUTANTS, CHEMICAL;

EID: 85020933906     PISSN: 01697722     EISSN: 18736009     Source Type: Journal    
DOI: 10.1016/j.jconhyd.2017.06.003     Document Type: Article

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