According to GlobalData’s company profile on Bank of New York Mellon, corrosion resistant battery packaging was a key innovation area identified from patents. Bank of New York Mellon's grant share as of June 2023 was 1%. Grant share is based on the ratio of number of grants to total number of patents.

Predicting communication settlement times across disparate computer networks

Source: United States Patent and Trademark Office(USPTO). Credit: The Bank of New York Mellon Corp

A recently filed patent (Publication Number: US20230196218A1) describes a system and method for predicting communication settlement times across different computer networks. The system includes storage circuitry that stores a machine learning architecture consisting of a first machine learning model, a second machine learning model, and an aggregation layer. The system also includes control circuitry that receives data feeds corresponding to different types of communication data and generates feature inputs based on these data feeds. The feature inputs are then inputted into the machine learning models to generate outputs. Using the aggregation layer, a third feature input is generated based on the outputs. The system determines a rule set for predicting communication settlement times based on the third feature input and uses this rule set to predict settlement times for incoming communications. The system also determines the aggregated communication load and required performance availability based on the settlement times, and provides recommendations based on these determinations. The recommendations are displayed on a user interface.

The method described in the patent involves receiving data feeds corresponding to different types of communication data and generating feature inputs based on these feeds. The feature inputs are then inputted into machine learning models to generate outputs. Using an aggregation layer, a third feature input is generated based on the outputs. The method determines a rule set for predicting communication settlement times based on the third feature input and uses this rule set to predict settlement times for incoming communications. The method also includes determining the aggregated communication load and comparing it to a threshold to determine recommendations. The method can be used to predict settlement times for multiple communications and provides recommendations based on these predictions.

In summary, the patent describes a system and method for predicting communication settlement times across different computer networks using machine learning models and rule sets. The system and method take into account various types of communication data and generate recommendations based on the predicted settlement times and aggregated communication load. This technology has the potential to improve communication efficiency and performance across disparate computer networks.

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