Application of a data mining approach to derive operating rules for the Eleviyan irrigation reservoir

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Abstract

Sattari MT, Apaydin H, Ozturk F, Baykal N. 2012. Application of a data mining approach to derive operating rules for the Eleviyan irrigation reservoir. Lake Reserv Manage. 28:142-152. Optimum irrigation reservoir operation is a significant issue for water management decision makers. In this study, we used 4 different datasets of monthly amounts of water to be released from the Eleviyan irrigation reservoir in Iran as inputs in a data mining model; "if-conditional" operating rules were determined as outputs. Operating rules derived from data mining and rules obtained from an optimization model were in high concordance, especially between the 2 datasets from the preconstruction period, with differences in only 12 of 252 instances (252 months) used to compare the 2 methods. Operating rules determined for the preconstruction period using the data mining method were also consistent with optimum operating rules determined either by optimization or Monte Carlo simulation. Thus, we concluded that the decision tree subtechnique of data mining is an appropriate method for determining meaningful operating rules for the reservoir. © Copyright by the North American Lake Management Society 2012.

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Sattari, M. T., Apaydin, H., Ozturk, F., & Baykal, N. (2012). Application of a data mining approach to derive operating rules for the Eleviyan irrigation reservoir. Lake and Reservoir Management, 28(2), 142–152. https://doi.org/10.1080/07438141.2012.678927

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