US 12,182,178 B1Granted

System and methods for varying optimization solutions using constraints based on an endpoint

AssigneeThe Strategic Coach Inc.

InventorsBarbara Sue Smith, Daniel J. Sullivan

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Abstract

A system for varying optimization solutions using constraints based on an endpoint, the system including at least a processor, a memory communicatively connected to the at least a processor, the memory containing instructions configuring the processor to receive process data including a plurality of impediments, generate an endpoint using a module configured to, analyze the plurality of impediments by extracting a feature from each impediment of the plurality of impediments, classify a plurality of impediments using the extracted features to a plurality of identifiers, rank the plurality of identifiers based on severity score, output the endpoint based on an identifier severity score, identify a plurality of nodes, receive at least a constraint, locate in the plurality of nodes an outlier cluster based on the endpoint, determine an outlier process as a function of the outlier cluster, and determine a visual element data structure as a function of the outlier process.

Claims18

Dependent claims

A system for varying optimization solutions using constraints based on an endpoint, the system comprising:

at least a processor;
a memory communicatively connected to the at least a processor, the memory containing instructions configuring the processor to:
receive process data comprising a plurality of impediments;
generate an endpoint using a module configured to:
analyze the plurality of impediments by extracting a feature from each impediment of the plurality of impediments;
classify a plurality of impediments using the extracted features to a plurality of identifiers;
rank the plurality of identifiers based on an identifier severity score;
output the endpoint based on the identifier severity score;
identify a plurality of nodes;
receive at least a constraint;
locate, in the plurality of nodes, an outlier cluster based on the endpoint, wherein locating the outlier cluster comprises:
identifying a target process;
inputting the target process and the plurality of nodes into an impact metric machine learning model;
receiving an impact metric from the impact metric machine learning model;
and
determining the outlier cluster as a function of the impact metric;
determine an outlier process as a function of the outlier cluster;
and
determine a visual element data structure as a function of the outlier process.

16 more elements

A method for varying optimization solutions using constraints based on an endpoint, the method comprising:

receiving, by a computing device, process data comprising a plurality of impediments;
generating, by the computing device, an endpoint using a module configured to:
analyze the plurality of impediments by extracting a feature from each impediment of the plurality of impediments;
classify a plurality of impediments using the extracted features to a plurality of identifiers;
rank the plurality of identifiers based on an identifier severity score;
output the endpoint based on the identifier severity score;
identifying, by the computing device, a plurality of nodes;
receiving, by the computing device, at least a constraint;
locating, by the computing device, in the plurality of nodes an outlier cluster based on the endpoint, wherein locating the outlier cluster comprises:
identifying a target process;
inputting the target process and the plurality of nodes into an impact metric machine learning model;
receiving an impact metric from the impact metric machine learning model;
and
determining the outlier cluster as a function of the impact metric;
determining, by the computing device, an outlier process as a function of the outlier cluster;
and
determining, by the computing device, a visual element data structure as a function of the outlier process.

14 more elements

Dependencies are inferred from the claim text.