Fuzzy logic can be applied in various domains such as control systems, decision-making processes, and pattern recognition. For instance, in control systems, fuzzy logic allows for more flexibility by incorporating imprecise inputs and linguistic rules. It can also be used in traffic signal optimization, where the timing of lights can vary based on real-time traffic conditions.

Fuzzy logic has proven useful in natural language processing, especially in sentiment analysis and language translation tasks. By handling uncertainty and ambiguity in language, fuzzy logic can provide more accurate results. Additionally, in medical diagnosis, fuzzy logic can account for the imprecise nature of symptoms and help determine the likelihood of different diseases.

Another interesting application of fuzzy logic is in weather forecasting. Weather conditions often involve degrees of certainty, such as 'partly cloudy' or 'mostly sunny.' Fuzzy logic can model these uncertainties and make predictions based on the fuzzy relationships between different weather variables.

Fuzzy logic finds application in recommendation systems, where it can handle the vagueness and subjectivity of user preferences. By using fuzzy sets and membership functions, recommendations can be tailored to individual users, taking into account their varying levels of interest or satisfaction.