Reservoir operating using Fuzzy Inference System and clustering (Case study: Ilanjogh Dam)
Author(s):
Abstract:
Results of a Non-Linear Programming (NLP) model were used to develop Fuzzy Rule Bases for optimal Ilanjogh reservoir operation located in Daregaz, northeast of Iran. The dam is desiged for agriculture of three crops (winter, barley, and sorghum). Making decision is considered in two levels: reservoir and farm levels. The reservoir level Fuzzy logic model extracts important features of the system from the input-output data set by NLP and represents features as general operating rules. The developed model serves not only as efficient decision making tool in easy and understandable Fuzzy Inference Systems, but also provides operators with a limited number of the most meaningful operating rules using Clustering-Based approach. The model is set properly in a yearly based with initial storage and monthly steps. Results showed that the changing trend of water releases in both models is the same with R2=0.97 such that over the 12 months period, both trends had increased from October to May but since then, they decreased gradually. But in general, the amount of annual released water in Fuzzy model is almost less than NLP, especially in competitive month, May and June, when there was a competition between all 3 crops for water, the percentage of water deficit to the percentage of annual mean water deficit were 0.57 and 0.81 in training and 0.93 and 1.145 in the test stage, respectively.
Keywords:
Language:
Persian
Published:
Water and Soil Conservation, Volume:18 Issue: 4, 2012
Page:
103
https://www.magiran.com/p1012075
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