Present Train Delay Prediction Systems (TDPS) tools are not best in class and procedures for taking care of and removing important data from large proportion of internal railway data and externaldata created by external miracles information available. Moreover these toolsare not organized in order to deal with the built-in temporal nature of changes such as changes in the apparent schedule. The influencing factor for writing this paper is to improve the proficiency of train-delay prediction. Here we propose a hybrid model mix of artificial neural networks with a genetic algorithms to build up the prediction model.
Volume 12 | 07-Special Issue
Pages: 2900-2903
DOI: 10.5373/JARDCS/V12SP7/20202433