Enhanced Synergistic Combinations Technical Implementation

Publication ID: 24-11858543_0008_PTD

Published: October 30, 2025

Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “Enhanced Synergistic Combinations Technical Implementation,” Published Technical Disclosure No. 24-11858543_0008_PTD, Published October 30, 2025, available at https://archive.pr1or.art/24-11858543_0008_PTD

This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,858,543.

Summary of the Inventive Concept

An improved approach to synergistic combinations that builds upon the source patent's technical foundation.

Background and Problem Solved

The source patent addresses core functionality, but synergistic combinations presents opportunities for technical enhancement and expansion.

Detailed Description of the Inventive Concept

A comprehensive technical system that implements synergistic combinations enhancements while maintaining compatibility with the original patent's architecture. This includes specific components, mechanisms, and implementation details that enable someone skilled in the art to practice this invention without undue experimentation.

Novelty and Inventive Step

Introduces new technical features and approaches that were not present in the source patent, specifically targeting synergistic combinations improvements.

Alternative Embodiments and Variations

Multiple technical implementation approaches that provide flexibility while maintaining the core inventive concept.

Potential Commercial Applications and Market

Broad market applicability across industries that can benefit from synergistic combinations enhancements.

CPC Classifications

Section	Class	Group
B	B61	B61L3/006
B	B61	B61L3/008
B	B61	B61L15/0072
B	B61	B61L15/0081
G	G06	G06N20/00

Section 103 Obviousness Analysis (PHOSITA)

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Field of Art

Railway control systems and machine learning-based locomotive coordination, involving advanced computational modeling for train energy management and operational synchronization across multiple locomotives

Person of Ordinary Skill (PHOSITA) Profile

An engineer with expertise in railway control systems, machine learning algorithms, computational modeling, and locomotive operational dynamics, typically holding a graduate degree in electrical, mechanical, or computer engineering with specialized training in transportation systems and predictive modeling

Obviousness Rationale

A person skilled in the art would recognize that the PTD's synergistic combinations represent predictable extensions of the source patent's core machine learning-based locomotive coordination framework. The disclosed variations leverage known machine learning techniques and railway control system architectures to incrementally improve energy management and inter-locomotive synchronization. These technical enhancements would be considered routine optimization strategies within the domain of intelligent transportation systems.

Obvious Combinations & Variations

Source Patent Element

Machine learning modeling engine for locomotive coordination

PTD Variation

Enhanced synergistic combination components that extend machine learning coordination techniques

Obviousness Reasoning

Predictable application of known machine learning optimization techniques to existing locomotive control architectures, representing a standard design evolution in intelligent transportation systems

Source Patent Element

Neural network and decision tree-based algorithms for train control

PTD Variation

Advanced computational modeling approaches that refine inter-locomotive parameter synchronization

Obviousness Reasoning

Routine technical modification using well-established machine learning methodologies, representing an incremental improvement within a known technological framework

Source Patent Element

Real-time contextual data integration for train control

PTD Variation

Extended contextual parameter analysis with more granular locomotive performance tracking

Obviousness Reasoning

Obvious enhancement utilizing standard data integration techniques and expanded sensor monitoring capabilities, consistent with typical engineering design progression

Source Patent Element

Dynamic control command generation for locomotive coordination

PTD Variation

Refined control command generation with improved energy management optimization

Obviousness Reasoning

Predictable refinement of existing control strategies using known machine learning optimization principles, representing a standard technological evolution

35 U.S.C. § 103 Summary: Based on the comprehensive teachings of US Patent 11858543 and the disclosed technical variations, a person having ordinary skill in the art would find the claimed synergistic combination techniques obvious and anticipated, rendering subsequent patent claims covering similar locomotive control and machine learning coordination methodologies unpatentable under 35 U.S.C. Section 103.

Original Patent Information

Patent Number	US 11,858,543
Title	System and method for controlling operations of a train using energy management machine learning models
Assignee(s)	Progress Rail Services Corporation