State Estimation Using Qualitative Inference to Cut Simulation Time
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Solution Overview
Problem
The challenge is to reduce the large number of input value candidates for simulation models, particularly in complex systems where the scale of the monitoring target is large, leading to excessive simulation execution time and impractical estimation results within a realistic timeframe.
Innovation Solution
An estimation device and method that employs qualitative inference to determine a state estimation target portion and acquire candidate qualitative expression information, followed by quantitative state candidate setting to narrow down input values for the simulation model, using a combination of qualitative and quantitative expression information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of input value candidates for simulation model is increased to improve estimation accuracy, then the estimation precision is improved, but the simulation execution time increases excessively
Solution Approach 1:
The patent segments the estimation process into two distinct stages: (1) qualitative inference stage that narrows down candidate portions using qualitative relationships, and (2) quantitative estimation stage that performs simulation only on the narrowed-down candidates. This segmentation allows the system to maintain high estimation precision while significantly reducing the number of simulations required, thus solving the time precision trade-off.
Solution Approach 2:
The patent performs preliminary qualitative inference before quantitative simulation to pre-narrow down the candidate input values. By conducting this preliminary filtering action using qualitative relationships and expert knowledge, the system reduces the search space for subsequent quantitative simulations, thereby maintaining precision while reducing execution time.
2Adaptability or versatility
If the scale of monitoring target is increased to improve comprehensiveness of state estimation, then the estimation completeness is improved, but the device complexity increases
Solution Approach 1:
The patent segments the monitoring target into multiple portions and establishes qualitative relationships between them. This segmentation allows the system to handle large-scale complex systems by breaking them into manageable parts while maintaining comprehensive estimation through the qualitative relationship network that connects all portions.
Solution Approach 2:
The patent introduces qualitative relationships as intermediaries between monitoring target portions and simulation models. These qualitative relationships act as mediators that capture complex interactions without requiring full quantitative modeling, thereby reducing system complexity while maintaining estimation completeness.
3Productivity
If qualitative inference is used to narrow down candidate portions, then the number of simulation candidates is reduced, but the inference accuracy may be compromised
Solution Approach 1:
The patent merges qualitative inference results with quantitative simulation in a hybrid estimation approach. The qualitative inference narrows down candidate portions efficiently, while the subsequent quantitative simulation on these candidates ensures accuracy is maintained. This merging of qualitative and quantitative methods solves the efficiency-accuracy trade-off.
Solution Approach 2:
The patent implements a feedback mechanism where qualitative inference guides the selection of candidate portions for quantitative simulation, and the simulation results can refine the qualitative understanding. This feedback loop ensures that the simplification introduced by qualitative inference does not compromise overall inference accuracy.
Data Source
AI summary
An estimation device determines a state estimation target portion of a monitoring target based on qualitative inference that uses designated portion qualitative expression information qualitatively indicating a state of a designated portion of the monitoring target, and acquires state candidate qualitative expression information that qualitatively indicates a candidate for the state of the state estimation target portion. The estimation device acquires state candidate quantitative expression information that quantitatively indicates a candidate for the state of the state estimation target portion, based on the state candidate qualitative expression information.


