Q3) a) Explain the Merits and Demerits of Fuzzy Logic.

✅ Merits of Fuzzy Logic:

Point	Explanation
1. Handles Uncertainty	Deals with vague, imprecise, and noisy data effectively.
2. Human-like Reasoning	Uses linguistic terms (e.g., high, low, medium) like human thinking.
3. No Need for Precise Models	Works without complex mathematical modeling.
4. Simple Rule-based Approach	Uses intuitive IF-THEN rules for decision-making.
5. Flexible and Adaptive	Can adapt to changes in system behavior.
6. Robust Performance	Works well under variable conditions and inputs.
7. Integration Possible	Easily combined with ANN, GA, and other AI methods (hybrid systems).
8. Wide Applicability	Used in control systems, healthcare, robotics, smart devices, etc.

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❌ Demerits of Fuzzy Logic:

Point	Explanation
1. Rule Explosion	Large number of rules needed for complex systems.
2. Subjective Design	Depends on expert knowledge for rules and membership functions.
3. No Learning by Itself	Requires integration with ML/ANN for self-learning.
4. Not Suitable for Precise Systems	Not ideal where exact outputs are critical.
5. Difficult to Validate	Output interpretation can be uncertain in complex systems.

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Conclusion:

Fuzzy logic offers simplicity, flexibility, and human-like decision-making, but designing an efficient fuzzy system requires careful rule and function tuning. It works best in uncertain, real-world environments, not in highly deterministic systems.