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Prediction Model of Water Resources in Mine Area Based on Phase Space Reconstruction and Chaos Neural Network

机译:基于相空间重构和混沌神经网络的矿区水资源预测模型。

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In the process of social economic development, water resource is increasingly scarce because of unreasonable exploitation of groundwater resources. It has seriously hampered the economic and social development speed in mine area, and even caused a series of negative effects of serious environmental and ecological problems. In this paper, chaos theory is used to study the water resource system in mine area. By analyzing the phenomena of chaotic characteristics in water resource system, regional mine water resources safety model was constructed based on the phase space reconstruction coupled with the neural network. Through the application of the model to forecast future water resources consumption in Gejiu mine area, the predicted results not only verified the validity of the model, but also found a new approach to study water resources in mine area.
机译:在社会经济发展的过程中,由于对地下水资源的不合理开采,水资源越来越稀缺。严重制约了矿区经济社会发展速度,甚至造成了一系列严重的环境生态问题的负面影响。本文采用混沌理论对矿区水资源系统进行了研究。通过分析水资源系统混沌特征现象,基于相空间重构与神经网络相结合,建立了区域矿山水资源安全模型。通过该模型对葛旧矿区未来水资源消耗量的预测,不仅验证了该模型的有效性,而且为研究矿区水资源提供了新的思路。

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