Transfer Apparatus Selection Using Preference Performance Prognoses

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Solution Overview

Problem

Optimizing machine-learning outputs for large and varied datasets becomes untenable due to tradeoffs between sophistication and efficiency, particularly in selecting transfer apparatuses based on user preferences.

Innovation Solution

A computing device receives user preferences and generates performance prognoses for each candidate transfer apparatus using supervised and unsupervised machine-learning processes, training on historical data to select the most aligned candidate transfer apparatus through an objective function optimization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If machine-learning methods are used to optimize instructions for users from machine-learning outputs, then the sophistication of the system is improved, but the efficiency deteriorates due to the large and varied data requirements

Engineering Contradiction:

ImprovesophisticationVSAvoidefficiency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The patent segments the large and varied dataset into multiple smaller, organized data structures (first data structure, second data structure, etc.). Each data structure contains specific subsets of transfer apparatus information organized by different criteria, allowing the system to process and query data in manageable portions rather than handling the entire large dataset at once.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary organization and indexing of transfer apparatus data into structured formats before the actual selection process. By pre-organizing data into multiple data structures with different organization criteria, the system eliminates the need for complex real-time processing during user interactions, thereby improving efficiency while maintaining sophistication.

Inventive Principle:

Principle #10Preliminary action

2Adaptability or versatility

If multiple data structures are used to organize transfer apparatus information, then the adaptability to different user preferences is improved, but the device complexity increases

Engineering Contradiction:

Improveadaptability to user preferencesVSAvoiddata structure complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent creates multiple data structures that serve universal purposes - each data structure can be used independently or in combination with others to satisfy different user preferences. The first data structure, second data structure, and additional data structures all follow a consistent organizational pattern, allowing them to function as interchangeable components that collectively provide versatile query capabilities without requiring entirely separate systems for each preference type.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS12511573B2System and method for selecting a candidate transfer apparatus

Publication Date: 2025.12.30 HAMMEL

AI summary

A method for determining a transfer apparatus based on user preferences includes receiving, by a computing device, at least a transfer invocation and a plurality of user preferences and generating, by the computing device, and for each candidate transfer apparatus of a plurality of candidate transfer apparatuses, a plurality of performance prognoses corresponding to the plurality of user preferences. The method includes selecting, by the computing device, a candidate transfer apparatus as a function of the plurality of performance prognoses and providing, by the computing device, the selected candidate transfer apparatus to a user.