Pros and Cons of Fuzzy Logic
Fuzzy logic is frequently used in machine controllers and artificial intelligence and can also be applied to trading software. Although it has a wide range of applications, it also has substantial limitations.
Because fuzzy logic mimics human decision-making, it is most useful for modeling complex problems with ambiguous or distorted inputs. Due to the similarities with natural language, fuzzy logic algorithms are easier to code than standard logical programming, and require fewer instructions, thereby saving on memory storage requirements.
These advantages also come with drawbacks, due to the imprecise nature of fuzzy logic. Since the systems are designed for inaccurate data and inputs, they must be tested and validated to prevent inaccurate results.
Pros and Cons of Fuzzy Logic
Fuzzy logic is more likely to reflect real-world problems than classical logic.
Fuzzy algorithms require broad validation and verification.
Fuzzy logic algorithms have lower hardware requirements than classical boolean logic.
Fuzzy control systems are dependent on human expertise and knowledge.
Fuzzy algorithms can produce accurate results with imprecise or inaccurate data.
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