Abstract
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.
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Jiang, Z., Zhang, S., Xin, R., Cheng, S., Li, N. (2012). Research of the Urban Air Quality Forecast Method Based on Resource Allocation Network. In: Lei, J., Wang, F.L., Deng, H., Miao, D. (eds) Artificial Intelligence and Computational Intelligence. AICI 2012. Lecture Notes in Computer Science(), vol 7530. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33478-8_80
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DOI: https://doi.org/10.1007/978-3-642-33478-8_80
Publisher Name: Springer, Berlin, Heidelberg
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