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Investigation of factors affecting rural drinking water consumption using intelligent hybrid models

water Science and Engineering 2023年第2期16卷 175-183页

作者： Alireza Mehrabani Bashar Hamed Nozari Safar Marofi Mohamad Mohamadi Ahad Ahadiiman Department of water Science and Engineering Faculty of AgricultureBu-Ali Sina UniversityHamedan 65178-38695Iran University of Kurdistan Sanandaj 66177-15175Iran sustainable development office of hamedan water and wastewater company Hamedan 65159-14478Iran

Identifying the factors affecting drinking water consumption is essential to the rational management of water resources and effective environment protection. In this study, the effects of the factors on rural drinking water demand were studied using the adaptive neuro-fuzzy inference system (ANFIS) and hybrid models, such as the ANFIS-genetic algorithm (GA), ANFIS-particle swarm optimization (PSO), and support vector machine (SVM)-simulated annealing (SA). The rural areas of Hamadan Province in Iran were selected for the case study. Five drinking water consumption factors were selected for the assessment according to the literature, data availability, and the characteristics of the study area (such as precipitation, relative humidity, temperature, the number of subscribers, and water price). The results showed that the standard errors of ANFIS, ANFIS-GA, ANFIS-PSO, and SVM-SA were 0.669, 0.619, 0.705, and 0.578, respectively. Therefore, the hybrid model SVM-SA outperformed other models. The sensitivity analysis showed that of the parameters affecting drinking water consumption, the number of subscribers significantly affected the water consumption rate, while the average temperature was the least significant factor. water price was a factor that could be easily controlled, but it was always one of the least effective parameters due to the low water fee.

关键词： ANFIS water distribution network Simulated annealing algorithm Support vector machine Adaptive neuro-fuzzy inference system

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