Selecting Parameter-Optimized Surrogate Models in DNAPL-Contaminated Aquifer Remediation Strategies

Environmental Engineering Science

Volumn 32, Issue 12, 2015, Pages 1016-1026

  Hou, Zeyu ^a,b   Lu, Wenxi ^a,b   Chu, Haibo ^a,b   Luo, Jiannan ^a,b  

^a Jilin University   (China)

^b JILIN UNIVERSITY   (China)

Author keywords

DNAPLs; parameter optimization; simulation optimization; surrogate model

Indexed keywords

ALGORITHMS; AQUIFERS; FUEL ADDITIVES; GENETIC ALGORITHMS; GROUNDWATER POLLUTION; HEALTH RISKS; IMPURITIES; INTERPOLATION; NEURAL NETWORKS; OPTIMIZATION; PARAMETER ESTIMATION; POLLUTION; RADIAL BASIS FUNCTION NETWORKS; SIMULATED ANNEALING;

ADAPTIVE PARTICLE SWARM OPTIMIZATIONS; DNAPLS; LATIN HYPERCUBE SAMPLING METHODS; PARAMETER OPTIMIZATION; RADIAL BASIS FUNCTION ARTIFICIAL NEURAL NETWORKS; SIMULATION OPTIMIZATION; SURFACTANT ENHANCED AQUIFER REMEDIATION; SURROGATE MODEL;

PARTICLE SWARM OPTIMIZATION (PSO);

AQUIFER; ARTICLE; ARTIFICIAL NEURAL NETWORK; ECOSYSTEM RESTORATION; ENVIRONMENTAL PARAMETERS; GENETIC ALGORITHM; KRIGING; NONAQUEOUS PHASE LIQUID; SIMULATION; SUPPORT VECTOR MACHINE;

EID: 84947909371     PISSN: 10928758     EISSN: 15579018     Source Type: Journal    
DOI: 10.1089/ees.2015.0055     Document Type: Article

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