whale algorithm

Due to the water situation in the country and on the other hand the increase in water needs, water resources management is important. Since the major share of water consumption is allocated to the agricultural sector, water allocation is one of the issues that should be considered. In the present study, a new and at the same time high-performance method based on the Whale algorithm (WOA), for the optimal allocation of water resources of Sufi-chai irrigation and drainage network located in East Azerbaijan province in the agricultural sector during the statistical year data were used from 2005 to 2013. The whale algorithm is one of the newest meta-heuristic algorithms inspired by the bubble net hunting method performed by humpback whales. The results were compared with the results of the ICA algorithm. The objective function was determined based on each of the products and their performance and the income from each product, and then the maximization of the objective function and the optimal allocation of water resources was performed by WOA and ICA algorithms. The results showed that by increasing the application coefficient to 0.9, the profit from the optimal water allocation is associated with a 30% increase in economic profit. Meanwhile, the WOA algorithm, compared to the ICA algorithm with an allocation of 1720 MCM per year, has 8.90% of the optimal use of water resources in agriculture. In general, the use of intelligent evolutionary methods can be a good solution for optimal water allocation in the agricultural sector.

The use of labyrinth weirs is one of the most effective and economical ways to increase weir efficiency by enhancing weir crown length, so that at a specified width and hydraulic height compared to other weirs, more discharge passes. In this study, the hybrid method of the Whale optimization algorithm and the fuzzy neural- inference system to estimate the optimal discharge coefficient of labyrinth weirs with the curved plan is introduced. In the proposed method, the efficiency and convergence of the Whale algorithm have been measured. The experimental data were used to validate the proposed method. The performance of the proposed method was evaluated with four statistics, including the correlation coefficient (R2), the root means square error (RMSE), the mean absolute error (MAE) and the efficiency criterion (NSE). The results indicate a good match between the observed and estimated values. The results of the WOA-ANFIS method with (H /P) and (θ), showed that the discharge coefficient of labyrinth weirs with the curved plan (Cd=0.786) in compared to labyrinth weirs with a triangular plan (Cd=0.682), it increases by 10%. Also, statistical analyzes performed on the obtained results showed that the WOA-ANFIS method with high values of RMSE = 0.021, R2 = 0.981, MAE = 0.010 and NSE = 0.976 has high efficiency in estimating the discharge coefficient of this type of weirs.