Application of ANN and ANFIS models for reconstructing missing flow data

Environmental Monitoring and Assessment

Volumn 166, Issue 1-4, 2010, Pages 421-434

  Dastorani, Mohammad T ^a   Moghadamnia, Alireza ^b   Piri, Jamshid ^c   Rico Ramirez, Miguel ^d  

^a YAZD UNIVERSITY   (Iran)

^b UNIVERSITY OF ZABOL   (Iran)

^c Jahad Keshavarzi of Sistan Region ^*  (Iran)

^d UNIVERSITY OF BRISTOL   (United Kingdom)

Author keywords

Artificial neural networks; Data gap filling; Hydrological data; Neuro fuzzy systems

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; ANFIS MODEL; ARID LANDS; ARTIFICIAL NEURAL NETWORK; DATA GAP; EFFICIENT METHOD; FEASIBILITY STUDIES; FLOW DATA; GAUGING STATIONS; HETEROGENEOUS DATA; HYDROLOGICAL DATA; MISSING DATA; NEUROFUZZY SYSTEM; RATIO METHOD; REAL-TIME DECISION MAKING;

DECISION MAKING; DEVELOPING COUNTRIES; FILLING; FORECASTING; FUZZY INFERENCE; FUZZY SETS;

FUZZY NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; FUZZY MATHEMATICS; HYDROLOGICAL MODELING; RECONSTRUCTION;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CALCULATION; CONTROLLED STUDY; DATA ANALYSIS; FUZZY SYSTEM; HYDROLOGY; INFORMATION PROCESSING; INTERMETHOD COMPARISON; MACHINE LEARNING; PREDICTION;

DATA INTERPRETATION, STATISTICAL; DECISION SUPPORT TECHNIQUES; ENVIRONMENTAL MONITORING; FEASIBILITY STUDIES; NEURAL NETWORKS (COMPUTER); WATER SUPPLY;

EID: 77954144514     PISSN: 01676369     EISSN: 15732959     Source Type: Journal    
DOI: 10.1007/s10661-009-1012-8     Document Type: Article

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