Forecasting arrival times of a vehicle at many downstream stops is very important in many cases. For multi-stop arrival time prediction, direct approaches and iterative approaches possess respective merits. Therefore, a hybrid method that has both direct and iterative modeling abilities is presented to forecast arrival times at multiple stops. The hybrid method consists of an iterative support vector machine (SVM)-based prediction model and a direct SVM-based prediction model. In hybrid model, output from the iterative model is a rough prediction and it also needs to be adjusted, based on output from the direct model. The proposed model is assessed with the data of transit route number 3 in Guiyang city, China. Results show that the hybrid model seems to be a powerful tool for multi-stop arrival time prediction.
In this paper we apply the notion of the product $MV$-algebra in accordance with the definition given by B. Riečan. We investigate the convex embeddability of an $MV$-algebra into a product $MV$-algebra. We found sufficient conditions under which any two direct product decompositions of a product $MV$-algebra have isomorphic refinements.