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Feature: Extend the library to support Type-2 fuzzy logic, which handles higher levels of uncertainty by using fuzzy membership functions themselves as fuzzy sets.
Benefit: Type-2 fuzzy logic is more robust for AI applications where data is highly uncertain or noisy, such as in sensor data fusion or natural language processing.
Example: A Type-2 fuzzy logic system could be used to improve the accuracy of sentiment analysis in text data.
The text was updated successfully, but these errors were encountered:
Feature: Extend the library to support Type-2 fuzzy logic, which handles higher levels of uncertainty by using fuzzy membership functions themselves as fuzzy sets.
Benefit: Type-2 fuzzy logic is more robust for AI applications where data is highly uncertain or noisy, such as in sensor data fusion or natural language processing.
Example: A Type-2 fuzzy logic system could be used to improve the accuracy of sentiment analysis in text data.
The text was updated successfully, but these errors were encountered: