The invention discloses a railway daily passenger volume acquisition method based on data correction, which comprises the following steps: acquiring a daily passenger volume data set in a historical time period according to a prediction demand, and determining a holiday and festival continuation period according to a daily passenger volume fluctuation amplitude change rate; decomposing the daily passenger volume data set into a plurality of modal components according to influence factors; carrying out trend prediction on the modal components respectively, and obtaining and reconstructing corresponding prediction modal components to form correction values; and decomposing the corrected daily passenger transport volume data set into a plurality of modal components according to influence factors, and predicting and reconstructing to form a daily passenger transport volume predicted value under the current prediction requirement. The technical scheme of the invention aims at conditions that the number of influence factors is large and the prediction work difficulty is large in the current prediction work of railway daily passenger transport. Data correction is conducted on the passenger flow of holidays and festivals, then the passenger flow is decomposed into modal components representing the multiple influence factors to be predicted and then synthesized, and the daily passengerflow prediction accuracy is greatly improved.