AUTO-HYPOTHESES ITERATION TO CONVERGE INTO SITUATION-SPECIFIC SCIENTIFIC CAUSATION USING INTUITION TECHNOLOGY FRAMEWORK
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United States of America
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May 5, 2022
app pub date -
Jan 18, 2022
filing date -
Jan 18, 2022
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Abstract
Methods and systems correlating hypotheses outcomes using relevance scoring for intuition based forewarning are disclosed. For one example, an intuition based forewarning method includes collecting and storing core data and surroundings data, wherein the core data includes parameters describing a system and ring data includes parameters describing surroundings of the system. The collected core data and ring data are analyzed to determine one or more changing situations of the system. A relevance score is provided for each determined changing situation of the system based on the analyzed core data and ring data. Each determined situation is correlated with one or more hypotheses outcomes representing a future system state based on the relevance score. The hypotheses may be modified using, for example, auto-hypothesis generation. A system forewarning is generated based on the correlated hypotheses outcomes which can be observed by one or more users.
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