Soft computing techniques toward modeling the water supplies of Cyprus

Neural Networks

Volumn 24, Issue 8, 2011, Pages 836-841

  Iliadis, L ^a   Maris, F ^a   Tachos, S ^b  

^a DEMOCRITUS UNIVERSITY OF THRACE   (Greece)

^b ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

Author keywords

5 fold cross validation; Artificial neural networks; Kernel algorithms; Support vector machines; Water supply

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CROSS VALIDATION; FUZZY PARTITION; INPUT PARAMETER; KERNEL ALGORITHMS; REGRESSION SUPPORT VECTOR MACHINES; RELIABLE MODELS; RESEARCH EFFORTS; SOFT COMPUTING MODELS; SOFTCOMPUTING TECHNIQUES; SUPPORT VECTOR; SUPPORT VECTOR REGRESSIONS; TRAINING DATA SETS; WATER POLICIES; WATER RESOURCES MANAGEMENT;

SOFT COMPUTING; SUPPORT VECTOR MACHINES; WATER MANAGEMENT; WATER SUPPLY;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CYPRUS; FUZZY SYSTEM; MATHEMATICAL MODEL; POLICY; PRIORITY JOURNAL; QUALITY CONTROL; REGRESSION ANALYSIS; RELIABILITY; RESOURCE MANAGEMENT; SUPPORT VECTOR MACHINE; VALIDATION STUDY; WATER SUPPLY; WATERSHED MANAGEMENT;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTERS; CYPRUS; FUZZY LOGIC; GLOBAL WARMING; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES; WATER SUPPLY; WEATHER;

EID: 80051799113     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2011.05.016     Document Type: Article

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