Abstract: A method for predicting changes in fuel consumption due to alterations in train operations is disclosed. The method comprises: collecting a baseline train data of a first train, the baseline train data including first train parameters, first operational parameters, and a first fuel consumption of the first train; inputting the baseline train data into an artificial intelligence (AI) model; training an AI model with a second train data, the second train data includes second operational parameters and a second fuel consumption of the first train, the AI model is trained until a baseline operation is predictable; implementing operational changes from the baseline operation to a field train operation for a third train, the field train operation includes changes to the first train parameters and changes to the first operational parameters implemented in the third train; and predicting, utilizing the AI model, the fuel consumption of the third train.

Abstract: Systems and method for operating a train are described herein. The train may include a plurality of nodes configured to detect a plurality of train variables and a train controller. The train controller including a memory storing computer-executable instructions; and a processor. The processor may be configured to receive a train model which may be configured to be used by a computation engine of the train controller to generate an output. The output may be displayed on an output device on the train controller. A human-user may input an indication into the train controller indicating that the generated output may be insufficient. The node data may be collected at a result of the input and transmitted to a train model generator.

Abstract: Systems and method for operating a train are described herein. The train may include a plurality of nodes configured to detect a plurality of train variables and a train controller. The train controller including a memory storing computer-executable instructions; and a processor. The processor may be configured to receive a train model which may be configured to be used by a computation engine of the train controller to generate an output. The output may be displayed on an output device on the train controller. A human-user may input an indication into the train controller indicating that the generated output may be insufficient. The node data may be collected at a result of the input and transmitted to a train model generator.

Abstract: A method for predicting changes in fuel consumption due to alterations in train operations is disclosed. The method comprises: collecting a baseline train data of a first train, the baseline train data including first train parameters, first operational parameters, and a first fuel consumption of the first train; inputting the baseline train data into an artificial intelligence (AI) model; training an AI model with a second train data, the second train data includes second operational parameters and a second fuel consumption of the first train, the AI model is trained until a baseline operation is predictable; implementing operational changes from the baseline operation to a field train operation for a third train, the field train operation includes changes to the first train parameters and changes to the first operational parameters implemented in the third train; and predicting, utilizing the AI model, the fuel consumption of the third train.