System Model Comparison With Perturbed Data Normalization
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Solution Overview
Problem
Existing systems face challenges in accurately comparing system models due to differences in underlying assumptions and complexities, which affect the accuracy and fairness of the comparison results.
Innovation Solution
An apparatus and method that utilize a processor to receive system data, apply a perturbation function to modify the data, and compare model outputs using an optimization function to generate a state change output, facilitating a comprehensive evaluation of system models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If system models with different underlying assumptions and complexities are compared directly, then the comparison process is simple, but the accuracy and fairness of the comparison results deteriorate
Solution Approach 1:
The patent transforms system models by adjusting their parameters to a common reference state. This involves modifying model parameters such as scale factors, units, and normalization constants to ensure that models with different underlying assumptions and complexities can be compared on an equal basis, thereby improving accuracy without requiring excessive procedural complexity
Solution Approach 2:
The patent introduces an intermediary transformation layer that mediates between diverse system models and the comparison process. This intermediary component standardizes model representations by applying consistent transformation rules, allowing accurate comparisons while shielding the comparison logic from the complexity of individual model variations
2Reliability
If system models with different underlying assumptions and complexities are compared directly, then the comparison process is straightforward, but the fairness of the comparison results deteriorates
Solution Approach 1:
The patent applies parameter transformation to normalize models across different assumptions. By systematically adjusting parameters such as scaling factors, boundary conditions, and normalization constants, the patent ensures that no single model's assumptions provide an unfair advantage, thereby improving fairness while maintaining a structured comparison process
Solution Approach 2:
The patent creates an equipotential comparison framework where all system models are transformed to operate under equivalent conditions. This involves standardizing reference states, units, and measurement bases so that models with different underlying assumptions compete on equal footing, enhancing fairness without requiring ad-hoc adjustments for each comparison
Data Source
AI summary
An apparatus for determining system model comparison including a processor and a memory, wherein the processor is configured to receive a first plurality of system data, wherein the first plurality of system data represents a first state of a system, and a second plurality of system data representing a second of the system, output a first model output using a first model of the system and the second plurality of system data; calculate at least a perturbation function; modify the second plurality of system data using the at least a perturbation function; output a second model output using the second model of the system and the at least a perturbation function; compare the first model output to the second model output using an optimization function; and generate a state change output corresponding to the system using the comparison.