TY - GEN
T1 - Inflow forecasting for real-time reservoir operation using artificial neural network
AU - Kim, Taesoon
AU - Choi, Gian
AU - Heo, Jun Haeng
PY - 2009
Y1 - 2009
N2 - Artificial neural network (ANN) is used for inflow forecasting of reservoir up to the next 12 hours. Numerical weather forecasting information (RDAPS), recorded rainfall data, water level of upstream dam and stream gauge site, and inflow of the current time are employed as input layer's training values, and target value is +3, +6, +9, and +12 hours later inflow to Hwacheon reservoir in South Korea. Comparison result between ANN with RDAPS and without RDAPS shows that RDAPS information is useful for forecasting inflow of reservoir.
AB - Artificial neural network (ANN) is used for inflow forecasting of reservoir up to the next 12 hours. Numerical weather forecasting information (RDAPS), recorded rainfall data, water level of upstream dam and stream gauge site, and inflow of the current time are employed as input layer's training values, and target value is +3, +6, +9, and +12 hours later inflow to Hwacheon reservoir in South Korea. Comparison result between ANN with RDAPS and without RDAPS shows that RDAPS information is useful for forecasting inflow of reservoir.
UR - http://www.scopus.com/inward/record.url?scp=70350164201&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70350164201&partnerID=8YFLogxK
U2 - 10.1061/41036(342)499
DO - 10.1061/41036(342)499
M3 - Conference contribution
AN - SCOPUS:70350164201
SN - 9780784410363
T3 - Proceedings of World Environmental and Water Resources Congress 2009 - World Environmental and Water Resources Congress 2009: Great Rivers
SP - 4947
EP - 4955
BT - Proceedings of World Environmental and Water Resources Congress 2009 - World Environmental and Water Resources Congress 2009
T2 - World Environmental and Water Resources Congress 2009: Great Rivers
Y2 - 17 May 2009 through 21 May 2009
ER -