Open AccessPassenger Capacity of Underground Metro by the Use of Neural Network Program (NNP)
Author(s) -
Mai Moaz Eldeeb,
Akram soltan kotb,
H.S. Riad,
Mohamed Ashour
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.j9538.0881019
Subject(s) - headway , artificial neural network , computer science , schedule , operations research , line (geometry) , transport engineering , engineering , simulation , machine learning , mathematics , geometry , operating system
The present paper deals with studying on (GCUM) by the use of (NNP), consequently, the future passenger fluctuations can be well predicted and it will be helpful to make wise decisions for realizing the most safety and economic future operation.To attain this goal, a methodology was proposed to collect the necessary data and analyze them. These data were applied as the inputs into the Neural Network Program (NNP) for the two (GCUM) lines ‘1’ & ‘2’ to have two models as inputs and outputs, one for the 1st line and the other for the 2nd one, taking only into consideration, the input, and output variables which gave tolerances less 19% than that were obtained by applying excel program. Thus, it is easily to predict the future capacity for any predicted year, and the corresponding headway as well as to prepare an estimated schedule complies with the required future Rolling Stock (RS).