Linear Array Encoding for Risk Evaluation Logic States
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Solution Overview
Problem
Complexity in characterizing events with logical elements and relationships leads to intractable data structures, making it difficult to analyze and manipulate event probabilities effectively.
Innovation Solution
A method that encodes event data into a linear array, reducing complexity by representing logic states with binary output and input variables, minterms, maxterms, present and next state values, and calculating success probabilities for path groups and combinations to determine system success.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If events are characterized with logical elements and logical element relationships, then the system can represent complex event scenarios, but the data structure becomes intractably complex
Solution Approach 1:
The patent segments the complex logical element relationships into discrete logic states organized in a linear array. Each logic state represents a specific path between events with defined binary input/output variables, minterms, and maxterms. This segmentation transforms the intractable complex structure into manageable discrete units that can be systematically processed.
Solution Approach 2:
The patent changes the parameter representation by encoding logical element relationships into a standardized linear array format with specific parameters (binary variables, minterms, maxterms, present/next state values). This parameter transformation converts the intractable complex data structure into a tractable structured format suitable for computational analysis.
2Measurement precision
If logical element relationships are used to characterize events, then comprehensive event analysis is possible, but computational efficiency decreases
Solution Approach 1:
The patent segments the computational task into processing individual logic states within a linear array rather than processing complex interconnected logical element relationships. This segmentation enables systematic computation of success probabilities for each logic state and path group, improving computational efficiency while maintaining analysis comprehensiveness.
Solution Approach 2:
The patent transforms the computational parameters by representing logical relationships in a linear array format with explicit binary variables and state transitions. This parameter change enables efficient algorithmic processing of event probabilities through systematic evaluation of logic states and path combinations, significantly improving computational efficiency.
3Loss of information
If complex logical element relationships are maintained, then complete event characterization is achieved, but ease of manipulation decreases
Solution Approach 1:
The patent segments the complex logical relationships into discrete logic states with clearly defined components (binary variables, minterms, maxterms, state transitions). This segmentation maintains complete event characterization while dramatically improving ease of manipulation by providing a structured linear array format that can be systematically processed and modified.
Solution Approach 2:
The patent changes the data structure parameters from complex interconnected logical elements to a linear array of logic states with standardized parameters. This parameter transformation preserves complete event characterization information while enabling easier manipulation through systematic access and modification of individual logic state components.
Data Source
AI summary
For risk evaluation, a method encodes event data as a linear array that includes a plurality of logic states. The method estimates a success probability for each logic state and identifies path groups of the plurality of logic states. The logic states of each path group must all be healthy for each logic state to contribute to system success. The method further identifies each path combination of path groups and path nodes that result in system success. In addition, the method calculates a system success probability as a sum of success probabilities for each path combination. The success rate for each path combination is calculated as a product of the path group success probabilities for the path combination.