# Q4 · Fuzzy architecture [3]

Subject: Intelligent Systems II

Exam: M2

Reader: https://deep-learning-study-room.vercel.app/is2/#m2/mocks/m2-paper-v2-1/q4

Canonical: https://deep-learning-study-room.vercel.app/read/is2/m2/mocks/m2-paper-v2-1--q4/

Q1(a)+Q1(b) compulsory; any two of Q2–Q4. Answers immediately below each question.

**Confirmed M2 pattern:** Q1(a) [2] and Q1(b) [2] are compulsory. Attempt any two of Q2, Q3 and Q4, each worth 3 marks. The paper offers 13 marks; you attempt 10. These are newly written practice questions, not claims about the exact upcoming paper. Solutions are directly below each question; the teaching working is deliberately longer than a concise exam answer.

**Q4. Explain the architecture of a Mamdani fuzzy inference system with a fan-controller example.** [3 marks · Practice]

#### Answer

The fuzzifier maps crisp temperature and occupancy inputs to membership degrees. The knowledge base contains membership functions and IF–THEN rules. The inference engine combines antecedent degrees, applies each rule’s consequent and aggregates the inferred outputs. The defuzzifier converts this aggregate to a numerical fan speed. For example, IF temperature is High AND occupancy is High THEN fan speed is Very High.