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Prediction Of Water Quality Of Bicarbonate Mineral Water In WUDALIANCHI Based on BP Neural Network Model

机译:基于BP神经网络模型的五大连池碳酸氢矿泉水水质预测。

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In order to grasp the water quality change trend and predict the future water quality characteristics of the bicarbonate mineral water in WUDALIANCHI, using the measured data from 2008 to 2016 of north drink spring in WUDALIANCHI as the predicted sample, carbon dioxide, total soluble solids, strontium and metasilicic acid which can divide mineral water type as analysis factor, the BP neural network combination forecast model was contructed. The results showed that the BP neural network combination forecast model was obviously more precise and better than grey system model, its average relative error was controlled within 5%. The results indicated that the BP neural network combination forecast model can effectively predict the change trend of water quality of bicarbonate mineral water in WUDALIANCHI.
机译:为了掌握水质变化趋势并预测五大连池市碳酸氢盐矿泉水的未来水质特征,使用五大连池北部饮料泉2008年至2016年的测量数据作为预测样本,二氧化碳,总可溶性固形物,用锶和偏硅酸作为矿泉水类型作为分析因子,构建了BP神经网络组合预测模型。结果表明,BP神经网络组合预测模型明显优于灰色系统模型,其平均相对误差控制在5%以内。结果表明,BP神经网络组合预测模型可以有效预测乌达莲池碳酸氢盐矿泉水水质的变化趋势。

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