COMPARISON OF BAYESIANNEURAL NETWORK, ARTIFICIAL NEURAL NETWORK GENE EXPRESSION PROGRAMMING IN RIVER WATER QUALITY (CASE STUDY: BELKHVIACHAY RIVER)

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GHORBANI MOHAMMAD ALI; DEHGHANI REZA

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Journal: JOURNAL OF WATERSHED MANAGEMENT RESEARCH Year:2017 | Volume:8 | Issue:15 Page(s): 13-24

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Title

COMPARISON OF BAYESIANNEURAL NETWORK, ARTIFICIAL NEURAL NETWORK GENE EXPRESSION PROGRAMMING IN RIVER WATER QUALITY (CASE STUDY: BELKHVIACHAY RIVER)

Author(s)

GHORBANI MOHAMMAD ALI | DEHGHANI REZA | Issue Writer Certificate

Keywords

ARDEBILQ2

MODELQ1

PREDICTIONQ1

TOTAL DISSOLVED SOLIDSQ2

Abstract

The amount of TOTAL DISSOLVED SOLIDS (TDS) is an important factor in stream engineering, especially study of river water quality. This study estimates the TDS amount of Belkhviachayriver in Ardabil Province, using bayesian neural network-, gene smart and artificial neural network. Quality variables include hydrogen carbonate, chloride, sulfate, calcium, magnesium, sodium and inflow (Q) in monthly time scale during the period (1976-2009) as input and TDS were chosen as output parameters. The criteria of correlation coefficient, root mean square error and of Nash Sutcliff coefficient were used to evaluate and performance compare of MODELs. The results showed that however the MODELs could be used to estimate with reasonable accuracy the amount of dissolved solids in water deal, but regarding to accuracy, bayesian neural network MODEL with the highest correlation (0.966), minimum root mean square error (0.094ppm) and the Nash Sutcliff (0.998) were put in the verification phase.The results showed that the bayesian neural network MODEL to estimate high minimum and maximum values of dissolved solids in water.

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APA: Copy

GHORBANI, MOHAMMAD ALI, & DEHGHANI, REZA. (2017). COMPARISON OF BAYESIANNEURAL NETWORK, ARTIFICIAL NEURAL NETWORK GENE EXPRESSION PROGRAMMING IN RIVER WATER QUALITY (CASE STUDY: BELKHVIACHAY RIVER). JOURNAL OF WATERSHED MANAGEMENT RESEARCH, 8(15), 13-24. SID. https://sid.ir/paper/230377/en

Vancouver: Copy

GHORBANI MOHAMMAD ALI, DEHGHANI REZA. COMPARISON OF BAYESIANNEURAL NETWORK, ARTIFICIAL NEURAL NETWORK GENE EXPRESSION PROGRAMMING IN RIVER WATER QUALITY (CASE STUDY: BELKHVIACHAY RIVER). JOURNAL OF WATERSHED MANAGEMENT RESEARCH[Internet]. 2017;8(15):13-24. Available from: https://sid.ir/paper/230377/en

IEEE: Copy

MOHAMMAD ALI GHORBANI, and REZA DEHGHANI, “COMPARISON OF BAYESIANNEURAL NETWORK, ARTIFICIAL NEURAL NETWORK GENE EXPRESSION PROGRAMMING IN RIVER WATER QUALITY (CASE STUDY: BELKHVIACHAY RIVER),” JOURNAL OF WATERSHED MANAGEMENT RESEARCH, vol. 8, no. 15, pp. 13–24, 2017, [Online]. Available: https://sid.ir/paper/230377/en

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