This paper presents an application of feed-forward neural networks and RPROP algorithm to forecast a time series consisting of the average monthly liquid flow measured at Broşteni hydrometric station from the Motru River. The paper represents the Romanian contribution for one of the Technical Reports of INTAS Project no. 397: “Data Mining Technologies and Image processing: Theory and Applications”, Task 4: “The prognosis of harvest and the base of the weather- and geo-monitoring of a region”.
neural networks, liquid flow, time series prediction, RPROP learning algorithm.
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