The improvement of total organic carbon forecasting using neural networks discharge model

Environmental Technology

Volumn 30, Issue 1, 2009, Pages 45-51

  Yeon, I S ^a   Jun, K W ^b   Lee, H J ^c  

^a Chungbuk National University   (South Korea)

^b Kangwon National University   (South Korea)

^c Gangwon Provincial College 115   (South Korea)

Author keywords

Discharge; Forecasting; Neural networks; Prediction; Total organic carbon

Indexed keywords

DISCHARGE (FLUID MECHANICS); FORECASTING; ORGANIC CARBON; WATER LEVELS; WATER MANAGEMENT; WATER QUALITY;

ARTIFICIAL NEURAL NETWORK MODELING; DISCHARGE MODELING; DISCHARGE PREDICTIONS; MONITORING PARAMETERS; REAL-TIME MANAGEMENT; SIMULTANEOUS MEASUREMENT; TOTAL ORGANIC CARBON; WATER QUALITY MONITORING STATIONS;

NEURAL NETWORKS;

RIVER WATER;

DISCHARGE (FLUID MECHANICS); ORGANIC CARBON; REAL TIME CONTROL; RIVERS; WATER LEVELS; WATER QUALITY;

DISCHARGE; FORECASTING METHOD; TOTAL ORGANIC CARBON; WATER QUALITY;

ARTICLE; ARTIFICIAL NEURAL NETWORK; ENVIRONMENTAL MONITORING; FORECASTING; SOUTH KOREA; TOTAL ORGANIC CARBON; WATER QUALITY;

ASIA; EURASIA; FAR EAST; KANGWON; KOREA; PYEONGCHANG RIVER; SOUTH KOREA;

EID: 57449083654     PISSN: 09593330     EISSN: 1479487X     Source Type: Journal    
DOI: 10.1080/09593330802468780     Document Type: Article

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