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Literature review/Related works - hanie FL helps in problem solving in real life..What kind problemFL techniques used in problem solving..

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Literature Review/Related Works

Hanie FL helps in problem solving in real life. What kind of problem FL techniques are used in problem solving?

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It seems like you're asking about how Fuzzy Logic (FL) is used in problem-solving in real life, and what kind of problems it can solve. Here's a step-by-step answer:

  1. Understanding Fuzzy Logic (FL): Fuzzy Logic is a mathematical approach to problem-solving that deals with imprecise or vague inputs. It's a form of many-valued logic where the truth values of variables may be any real number between 0 and 1, unlike traditional binary sets (True or False).

  2. Real-life Applications of Fuzzy Logic: Fuzzy Logic has been used in a variety of real-life applications, including control systems, decision-making, and pattern recognition. For example, it's used in automatic control systems for household appliances like washing machines and dishwashers, where it helps to adjust the washing cycle based on the load size and dirtiness of the dishes or clothes. It's also used in automotive subsystems like ABS and cruise control.

  3. Problem-Solving with Fuzzy Logic: The kind of problems that Fuzzy Logic can solve are typically those that involve some level of uncertainty or ambiguity. For instance, it can be used to make decisions in situations where the information is incomplete or unclear. It's particularly useful in problems where an issue can't be addressed as simply true or false, but rather requires a degree of truth.

  4. Fuzzy Logic Techniques: There are several techniques used in Fuzzy Logic for problem-solving. These include Fuzzy Set Theory, Fuzzy If-Then Rules, Fuzzy Decision Making, and Fuzzy Inference Systems. These techniques help to model complex systems and make decisions based on fuzzy, imprecise, noisy, or missing information.

In conclusion, Fuzzy Logic is a powerful tool for problem-solving in real-life situations where traditional binary logic falls short. It's used in a wide range of applications and employs a variety of techniques to handle uncertainty and make decisions based on incomplete or imprecise information.

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