Paper Title
An Effective Method for Maintenance Scheduling of Vehicles Using Fast Supervised Learning

For effective operation of a transportation system design of the maintenance scheduling of vehicles has its own implication. At present, every transportation system recommends inspection based planning to deal maintenance activity of vehicles in a transportation system. These scheduling activities help the operator to organize maintenance activity along with identification of proactive failure situation. In order to avoid the dilemma like premature aging and failure of vehicles in transportation system responsible for spontaneous and costly maintenance charges, at regular intervals it is imperative to carry out preventive maintenance (PM). This paper presenting neural network approach, which has been used for application of scheduling, Scaled Conjugate Gradient Descent algorithm (SCGD) and Levenberg-Marquardt Method has been utilized and compared. Index Terms— Maintenance scheduling, Preventive maintenance, Neural network, supervised learning