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Research of the Urban Air Quality Forecast Method Based on Resource Allocation Network

机译:基于资源分配网络的城市空气质量预测方法研究

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An air quality forecast model based on the resource allocation network has been established in consideration of the time-varying characteristics of the urban air quality and the effects of a variety of nonlinear factors to the prediction accuracy. We have used the distance criteria and error criteria to allocate hidden layer nodes dynamically or adjust network parameters. In this way, we have got the minimum neural network structure to meet the error requirements and avoid solving the problem of selecting the initial neural network structure and parameters.
机译:考虑到城市空气质量的时变特征以及各种非线性因素对预测精度的影响,建立了基于资源分配网络的空气质量预测模型。我们使用了距离标准和错误标准来动态分配隐藏层节点或调整网络参数。这样,我们得到了最小的神经网络结构,可以满足误差要求,避免解决选择初始神经网络结构和参数的问题。

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