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Showing 2 results for Tarazkar

B. Najafi, M. Zibaei, M. H. Sheikhi, M. H. Tarazkar,
Volume 11, Issue 1 (spring 2007)
Abstract

In this study wholesale prices of selected crops, namely, tomato, onion and potatoes in Fars province were predicted for various time horizons by using common methods of forecasting and artificial neural networks (ANN). Monthly data from September 1998 to June 2005 period were obtained from Ministry of Jihad-e Agriculture. For comparing different methods data selected from September 1998 to December 2004 were utilized, and latest six - month data were mainly used to monitor the power of prediction. The MAE, MSE and MAPE criteria were used for comparing the ability of different forecasting methods. Results of this study showed that ANN had the lowest error in prediction of prices for one - to three - month periods, but for six - month prediction, all forecasting methods were not statistically different.
M. H. Tarazkar, M. Zibaei, G.r. Soltani, M. Nooshadi,
Volume 22, Issue 2 (Summer 2018)
Abstract

Nowadays, water resource management has been shifted from the construction of new water supply systems to the management and the optimal utilization of the existing ones. In this study, the reservoir operating rules of Doroodzan dam reservoir, located in Fars province, were determined using different methods and the most efficient model was selected. For this purpose, a monthly nonlinear multi-objective optimization model was designed using the monthly data of a fifteen-year period (2002-2017). Objective functions were considered as minimizing water scarcity index in municipal, industrial, environmental and agricultural sectors. In order to determine the operating rule curves of reservoir, in addition to the nonlinear multi-objective optimization model, the methods of ordinary least-squares regression (OLS), fuzzy inference system and adaptive network fuzzy inference system (ANFIS) were used. Also, the reliability, resiliency, vulnerability and sustainability criteria were used to compare the different methods of reservoir performance rules. The results showed that ANFIS model had the higher sustainability criterion (0.26) due to its greater reliability (0.7) and resilience (0.42), as well as its lower vulnerability (0.13), thereby showing the best performance. Therefore, ANFIS model could be effectively used for the creation of Doroodzan reservoir operation rules.


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