Evolutionary regression modeling with active learning: An application to rainfall runoff modeling

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5495 LNCS, Issue , 2009, Pages 548-558

  Couckuyt, Ivo ^a   Gorissen, Dirk ^a   Rouhani, Hamed ^b   Laermans, Eric ^a   Dhaene, Tom ^a  

^a GHENT UNIVERSITY   (Belgium)

^b UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE LEARNING; AUTOMATED APPROACH; COMPUTATIONAL COSTS; CONTROLLED EXPERIMENT; DESIGN SPACE EXPLORATION; DOMAIN EXPERTS; FEASIBLE ALTERNATIVES; HIGH-FIDELITY SIMULATIONS; HYPER-PARAMETER; KERNEL METHODS; MACHINE-LEARNING; MODEL ACCURACY; MODEL CALIBRATION; PROTOTYPING; RAINFALL-RUNOFF MODELING; REGRESSION MODEL; REGRESSION MODELING; SAMPLE SELECTION; SURROGATE MODEL; SURROGATE MODELING; TYPE SELECTION;

ALGORITHMS; FUEL ADDITIVES; LEARNING SYSTEMS; NEURAL NETWORKS; OPTIMIZATION; RAIN; REGRESSION ANALYSIS; RUNOFF; SENSITIVITY ANALYSIS; SPACE RESEARCH; VISUALIZATION;

COMPUTER SIMULATION;

EID: 78650729385     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04921-7_56     Document Type: Conference Paper

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