Ali Azizpor; Ahmad Rajabi; Fariborz Yosefvand; Saeid Shabanlou
Abstract
In the current study, a new hybrid of the genetic algorithm (GA) and adaptive Neuro-fuzzy inference system (ANFIS) was introduced to model the discharge coefficient (DC) of triangular weirs. The genetic algorithm was implemented for increasing the efficiency of ANFIS by adjusting membership functions ...
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In the current study, a new hybrid of the genetic algorithm (GA) and adaptive Neuro-fuzzy inference system (ANFIS) was introduced to model the discharge coefficient (DC) of triangular weirs. The genetic algorithm was implemented for increasing the efficiency of ANFIS by adjusting membership functions as well as minimizing error values. To evaluate the proficiency of the proposed hybrid method, the Monte Carlo simulations (MCS) and the k-fold validation method (k=5) was applied. The results of developed hybrid model indicate that the weir vortex angle, flow Froude number, the ratio of the weir length to its height, the ratio of the channel width to the weir length and ratio of the flow head to the weir height are the most effective parameters in the DC estimation. The quantitative examination of the proposed hybrid method indicates that the Root Mean Square Error (RMSE) and Mean Absolute Percent Error (MAPE) are as 0.016 and 1.647 (respectively) for the superior model. Besides, the Froude number is found as the most effective variable in DC modeling through the quantitative analysis. A comparison of the developed hybrid ANFIS-GA with the individual ANFIS model in the DC estimation indicates the hybrid model outperformed than the individual one.
Setareh Heydari; Jafar Mamizadeh; Javad Sarvarian; Goodarz Ahmadi
Abstract
The optimal design of urban water distribution networks is a significant issue that has been of critical interest in the water industry for many years. The optimal design of the distribution network aims to find the best solution for transferring water from the reservoir to consumers at the lowest cost. ...
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The optimal design of urban water distribution networks is a significant issue that has been of critical interest in the water industry for many years. The optimal design of the distribution network aims to find the best solution for transferring water from the reservoir to consumers at the lowest cost. In this study, optimization of the water distribution network (ZONE 1 of Ilam city, Iran) was performed using the fast messy genetic algorithms (FMGA) tool in the hydraulic model for three different pipe networks. Also, these networks were optimized by using a combination of EPANET and an in-house developed binary genetic algorithm in MATLAB. The costs of the optimized hydraulic networks of polyethylene and polypropylene pipes were lower, respectively, by 20.56 % and 52.94 % compared to the consulting company's original designs, while for the glass fiber reinforced plastic pipe (GRP) pipe network the cost increased by 12.61 %. Also, the results of a developed algorithm for polyethylene pipe decreased by 22.13 %.
Nasrin Abozari; Mohammadreza Hassanvand; Amir Hossein Salimi; Salim Heddam; Hossein Omidvar Mohammadi; Amir Noori
Abstract
The frequent occurrences of wet and dry in the catchment area of the Gamasiab river located in the west of Iran, in addition to affecting the quantitative status of surface water, has caused changes in the water quality of the basin. Therefore, modeling and prediction of Gamasiab river water quality ...
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The frequent occurrences of wet and dry in the catchment area of the Gamasiab river located in the west of Iran, in addition to affecting the quantitative status of surface water, has caused changes in the water quality of the basin. Therefore, modeling and prediction of Gamasiab river water quality in wet and dry periods are research priority. In this study, an optimized artificial neural network (ANN) trained with three different optimization algorithms namely; particle swarm optimization (PSO), genetic algorithm (GA) and imperialist competitive algorithm (ICA) was proposed for predicting the electric conductivity (EC). For this purpose, water quality data from 1967 to 2017 collected at the hydrometric station in the Gamasiab river were used for developing and testing the models. First, the study program was divided into two periods of wet and dry, this classification based on flow rate in the river. Then, in a preliminary statistical analysis, the effective parameters were determined for EC estimation. The performance of the applied methods showed that the ANN optimized using ICA algorithm was better than the ANN optimized with GA and PSO, and also the standard ANN without optimization. Overall, the ANN optimized with ICA has higher R and lower MARE and RMSE, with values of 11.56, 19.63 and 0.93, during the dry period, and 10.63, 17.19 and 0.97 during the wet period, respectively.
Mohammad Hossein Karimi Pashaki; Amir Khosrojerdi; Hossein Sedghi
Abstract
The water used in the production process of an agricultural or industrial product iscalled "virtual water". In Iran with low average annual precipitation also lack ofavailable water resources, concept of the virtual water and its trade is used as astrategy for optimal operation of water resources in ...
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The water used in the production process of an agricultural or industrial product iscalled "virtual water". In Iran with low average annual precipitation also lack ofavailable water resources, concept of the virtual water and its trade is used as astrategy for optimal operation of water resources in many fields such as waterscarcity, drought and so on. This concept, also, could hold some interesting newopportunities for the field of sustainable consumption. Recently, in Iran, net virtualwater import reached to (15-20)*109 m3 per year and is one out of the top ten virtualimporting countries. In this research, after virtual water applicable conceptsexpressing, virtual water content in some of the agricultural products in the worldhave been compared with products existence in Iran. Additionally, we selectedsome strategic agricultural products, which export and import to the country, andused an algorithm called "Genetic Algorithm", to optimize virtual water usage andtrade according to demands, agricultural situation, production cost andenvironmental condition. Results showed which products how could help optimalwater resources operation and effect of virtual water usage in economic growth.
