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/Systems And Methods To Generate Data Messages Indicating A Probability Of Execution For Data Transaction Objects Using Machine Learning
Abstract

A computer system includes a transceiver that receives over a data communications network different types of input data and multiple data transaction objects from multiple source nodes. A pre-processor processes the different types of input data and the data transaction objects to generate an input data structure. Based on the input data structure, one or more predictive machine learning models is trained and used to predict a probability of execution of each of the data transaction objects at a future execution time. Output data messages are then generated for transmission by the transceiver over the data communications network indicating the probability of execution for at least one of the data transaction objects at the future execution time.

Full Text

What is claimed is:

A computer system includes a transceiver that receives over a data communications network different types of input data and multiple data transaction objects from multiple source nodes. A pre-processor processes the different types of input data and the data transaction objects to generate an input data structure. Based on the input data structure, one or more predictive machine learning models is trained and used to predict a probability of execution of each of the data transaction objects at a future execution time. Output data messages are then generated for transmission by the transceiver over the data communications network indicating the probability of execution for at least one of the data transaction objects at the future execution time.
Timeline
Filed
03/05/2026
Published
07/09/2026
Granted
Not Available
IPC Codes(10)
G06N 20/20:Ensemble learning
G06F 18/231:Hierarchical techniques, i.e. dividing or merging pattern sets so as to obtain a dendrogram
G06F 18/2321:using statistics or function optimisation, e.g. modelling of probability density functions