Abstract

CHAOYANG, Shi  and  ZHANG, Zhen. A prediction method of regional water resources carrying capacity based on artificial neural network. Earth Sci. Res. J. [online]. 2021, vol.25, n.2, pp.169-177.  Epub Oct 15, 2021. ISSN 1794-6190.  https://doi.org/10.15446/esrj.v25n2.81615.

To better predict the water resources carrying capacity and guide the social and economic activities, a prediction method of regional water resources carrying capacity is proposed based on an artificial neural network. Zhaozhou County is selected as the research area of water resources carrying capacity prediction, and its natural geographical characteristics, social economy, and water resources situation are explored. According to the regional water resources quantity and utilization characteristics and evaluation emphasis, the evaluation index system of water resources carrying capacity is constructed to evaluate the importance and correlation of water resource carrying capacity. The pressure degree of water resources carrying capacity is divided into five grades. According to the evaluation standard of bearing capacity, the artificial intelligence BP neural network model is constructed. Based on the main impact factors of water resources carrying capacity in this area, the water resources carrying capacity grade is obtained by weight calculation and convergence iteration by using neural network model and influence factor data to realize the prediction of water resources carrying capacity. The research results show that the network model can meet the demand for precision. The prediction results have a high degree of fit with the actual data, indicating that human intelligence can obtain accurate prediction results in water resources carrying capacity prediction.

Keywords : Artificial neural network; BP neural network; Regional water resources; Water resources carrying capacity; Carrying capacity prediction.

        · abstract in Spanish     · text in English     · English ( pdf )