Transition Confidence Matrix for Dynamic State Validation
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Solution Overview
Problem
Existing methods for assessing the accuracy of state transitions in dynamic systems are laborious and time-consuming, particularly when relying on manual curation processes, which are impractical for providing timely confidence in state transitions.
Innovation Solution
A system and method that utilize a transition confidence matrix to provide confidence information associated with detected state transitions, allowing for automated validation of state transitions using historical data and real-time analysis, enabling faster and more accurate assessment of transition validity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual curation process is used to assess state transition accuracy, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary action by pre-computing and storing transition confidence metrics in a confidence matrix during an offline phase using historical data. This pre-computed matrix is then reused during real-time operation to quickly validate state transitions without requiring manual curation, thus resolving the time loss while maintaining measurement precision.
2Measurement precision
If manual curation process is used to assess state transition accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system creates a simplified copy of the complex manual assessment process by computing transition confidence metrics from historical data and storing them in a confidence matrix. This matrix serves as a reference copy that can be quickly queried during real-time operation, replacing the need for complex manual curation processes while maintaining assessment precision.
3Productivity
If unsupervised technique is used to determine state, then productivity is improved, but measurement precision worsens
Solution Approach 1:
The system implements feedback by using the pre-computed confidence matrix to validate and verify the outputs of the unsupervised state determination technique. The confidence metrics provide feedback on the reliability of each detected state transition, allowing the system to maintain high productivity from automated detection while ensuring measurement precision through confidence-based validation.
Data Source
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AI summary
A method includes obtaining, at a first device, first output from a transition state model for a dynamic system. The first output indicates a first state of the dynamic system. The method includes obtaining, at the first device, second output from the transition state model. The second output indicates a state transition from the first state to a second state. The method includes retrieving, at the first device, a transition confidence metric associated with the state transition from the first state to the second state from a transition confidence matrix. The method also includes providing, via the first device, the second state as output in response to the transition confidence metric indicating that the state transition is valid.