DEMAND FORECASTING FOR TRANSPORTATION SERVICES

Embodiments described herein are related to systems and methods for forecasting demands for a transportation service. In one aspect, a set of neural network models may be implemented, where each neural network model can be configured to predict a booking status of a category of carriers on a corresp...

Full description

Saved in:
Bibliographic Details
Main Authors NAGALLA, Durga, WISE, Tyler, CAMPOBASSO, Michael, LANPHEAR, William, HAGERTY, Zack, BLAKE, James
Format Patent
LanguageEnglish
French
German
Published 19.07.2023
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
Online AccessGet full text

Cover

More Information
Summary:Embodiments described herein are related to systems and methods for forecasting demands for a transportation service. In one aspect, a set of neural network models may be implemented, where each neural network model can be configured to predict a booking status of a category of carriers on a corresponding date from a range of dates before a departure date. In one aspect, for each neural network model, a corresponding set of configuration values can be determined. Examples of the corresponding set of configuration values includes at least one of a number of layers, a number of neurons, and an activation function of the each neural network model. The set of neural network models can be constructed, according to corresponding sets of configuration values, and the constructed neural network models can be trained.
Bibliography:Application Number: EP20230152210