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Research on prediction of water quality of water reservoir with combined Multiple Neural Networks model

机译:组合神经网络模型在水库水质预测中的应用

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Previously, it is not easy to solve problems like having a lot of Water Factors, being hard to express the whole process of change when use deterministic model to predict the water quality. In order to solve the problem, the essay founded and used BP and RBF, the predict model of combined Multiple Neural Networks to check and simulate the data of water quality monitoring of Fengman Reservoir on the Songhua River from 1985 to 2010. The result is that the prediction is obviously better than using previous Single Neural Network. The prediction is more accurate and practical. It can provide better support of decision on management of water environment of the reservoir.
机译:以前,要解决诸如具有大量水因子的问题并不容易,使用确定性模型预测水质时很难表达变化的整个过程。为了解决这一问题,本文建立了BP神经网络和RBF神经网络,并采用多神经网络组合预测模型对1985年至2010年松花江丰满水库水质监测数据进行了检验和模拟。结果是该预测显然比使用以前的单一神经网络要好。该预测更加准确和实用。它可以为水库水环境管理决策提供更好的支持。

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