Abstract:

According to the time-varying characteristics of the urban air quality, an air quality predicting model using the resource allocation neural network and the hidden layer nodes correlation pruning algorithm was established. The model had  simple structure and the online learning capability. Training and testing results showed that the model could not only reduce the complexity of the network structure, but obtain more accurate forecasting than the usual resource allocation neural network.

Key words:  resource allocation network; , correlation; , node synthesis; , air quality; , predicting