Atmospheric Visibility Prediction Based on Multi-Model Fusion

In this paper, a combinatorial algorithm-based visibility prediction method is proposed for improving the accuracy of visibility prediction. Firstly, four algorithms, namely support vector machine, kernel extreme learning machine, random forest and RBF neural network, are used as the basis functions for prediction, then the objective function of the combined prediction is constructed, the cuckoo search is used to optimise the calculation of the weighting coefficients of the combined prediction, and finally the combined prediction results are obtained. The experimental results show that the combined prediction algorithm proposed in this paper can effectively improve the accuracy of visibility prediction, and has certain application and research value.