Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China

Environmental Monitoring and Assessment

Volumn 185, Issue 5, 2013, Pages 4361-4371

  Wen, Xiaohu ^a   Fang, Jing ^b   Diao, Meina ^a,c   Zhang, Chuanqi ^a,c  

^a YANTAI INSTITUTE OF COASTAL ZONE RESEARCH   (China)

^b Chinese Academy of Sciences   (China)

^c UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

Author keywords

Artificial neural network; Dissolved oxygen; Heihe River; Modeling

Indexed keywords

ARTIFICIAL NEURAL NETWORK MODELING; BAYESIAN REGULARIZATION; COEFFICIENT OF CORRELATION; CORRELATION COEFFICIENT; ELECTRICAL CONDUCTIVITY; HEIHE RIVER; ROOT MEAN SQUARE ERRORS; WATER QUALITY PARAMETERS;

ALKALINITY; CALCIUM; CHLORINE COMPOUNDS; DISSOLVED OXYGEN; MEAN SQUARE ERROR; MODELS; NITROGEN; WATER QUALITY; WATER RESOURCES;

NEURAL NETWORKS;

CALCIUM; CHLORIDE; DISSOLVED OXYGEN; NITRATE; NITROGEN; RIVER WATER; SURFACE WATER; OXYGEN;

ALGORITHM; ALKALINITY; AMMONIA; AMMONIUM; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; BAYESIAN ANALYSIS; CALCIUM; CHLORIDE; CONCENTRATION (COMPOSITION); DISSOLVED OXYGEN; ELECTRICAL CONDUCTIVITY; HARDNESS; NITRATE; PH; RIVER WATER; WATER QUALITY;

ALKALINITY; ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYES THEOREM; CHINA; DEPENDENT VARIABLE; ELECTRIC CONDUCTIVITY; PH; RIVER; VALIDATION PROCESS; WATER HARDNESS; WATER QUALITY; WATER SAMPLING; WATER SUPPLY; ALGORITHM; CHEMICAL MODEL; CHEMISTRY; ENVIRONMENTAL MONITORING; METHODOLOGY; STATISTICS; WATER POLLUTANT; WATER POLLUTION;

CHINA; GANSU; HEI RIVER;

ALGORITHMS; BAYES THEOREM; CHINA; ENVIRONMENTAL MONITORING; MODELS, CHEMICAL; NEURAL NETWORKS (COMPUTER); NITROGEN; OXYGEN; RIVERS; WATER POLLUTANTS, CHEMICAL; WATER POLLUTION, CHEMICAL;

MLCS; MLOWN;

EID: 84878347590     PISSN: 01676369     EISSN: 15732959     Source Type: Journal    
DOI: 10.1007/s10661-012-2874-8     Document Type: Article

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