International business machines corporation (20240346106). SYMBOLIC MODEL DISCOVERY RECTIFICATION simplified abstract

SYMBOLIC MODEL DISCOVERY RECTIFICATION

Organization Name

international business machines corporation

Inventor(s)

Lior Horesh of North Salem NY (US)

Cristina Cornelio of Kilchberg (CH)

Sanjeeb Dash of Croton on Hudson NY (US)

Joao P. Goncalves of Wappingers Falls NY (US)

Kenneth Lee Clarkson of Madison NJ (US)

Nimrod Megiddo of Palo Alto CA (US)

Bachir El Khadir of White plains NY (US)

Vernon Ralph Austel of Cortlandt Manor NY (US)

SYMBOLIC MODEL DISCOVERY RECTIFICATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240346106 titled 'SYMBOLIC MODEL DISCOVERY RECTIFICATION

Simplified Explanation:

The method described in the patent application aims to refine a mis-specified symbolic model by utilizing data and constraints to generate partial expression trees and solve optimization problems for each tree, resulting in a refined symbolic model.

Key Features and Innovation:

• Refinement of mis-specified symbolic models
• Utilization of data and constraints
• Generation of partial expression trees
• Solution of optimization problems
• Creation of refined symbolic models

Potential Applications: This technology could be applied in various fields such as:

• Engineering
• Data analysis
• Process optimization
• Machine learning

Problems Solved:

• Correcting mis-specified symbolic models
• Enhancing accuracy of models
• Improving understanding of processes or phenomena

Benefits:

• Increased model accuracy
• Enhanced decision-making capabilities
• Improved process optimization

Commercial Applications: Title: "Enhanced Symbolic Model Refinement Technology for Process Optimization" This technology could be utilized in industries such as:

• Manufacturing
• Healthcare
• Finance
• Research and development

Prior Art: Readers interested in prior art related to this technology could explore research papers, patents, and academic journals in the fields of symbolic modeling, optimization, and data analysis.

Frequently Updated Research: Stay updated on the latest advancements in symbolic model refinement, optimization techniques, and data-driven modeling approaches to enhance the application of this technology.

Questions about Symbolic Model Refinement Technology: 1. How does this technology improve upon traditional model refinement methods? 2. What are the key factors to consider when applying this technology in different industries?

Original Abstract Submitted

a method for obtaining a refined model given a mis-specified symbolic model. the method includes receiving a mis-specified symbolic model and data pertaining to a process or phenomenon corresponding to the mis-specified symbolic model; receiving one or more constraints; generating a plurality of partial expression trees based on the mis-specified symbolic model; solving an optimization problem for each of the partial expression trees; and determining a refined symbolic model of the mis-specified symbolic model based on results of the optimization problem for each partial expression tree.