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Deep Learning in Transport Studies: A Meta-analysis on the Prediction Accuracy
2020
Journal of Big Data Analytics in Transportation
AbstractDeep learning methods are being increasingly applied in transport studies, while the methods require modellers to go through a try-and-error model tuning process particularly on choosing neural network structure. Moreover, the accuracy level also depends on other factors such as the type of data, sample size, region of data collection, and time of prediction. To efficiently facilitate such a model tuning process, this study attempts to summarize the relationship between the prediction
doi:10.1007/s42421-020-00030-z
fatcat:dbsovivksvfkvonsd3252bz534