# Re-examination · 25 Jun 2024

Subject: Intelligent Systems II

Exam: TEE

Reader: https://deep-learning-study-room.vercel.app/is2/#tee/papers/paper-2024-reexam

Canonical: https://deep-learning-study-room.vercel.app/read/is2/tee/papers-chapter/paper-2024-reexam/

Actual historical paper ·100 marks attempted /140 offered · Q1 compulsory + any four of Q2–Q7. Source defects and solution assumptions are explicitly identified.

1. [Q1(a) Traditional versus evolutionary optimization [5]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q1a/)
2. [Q1(b) Bayes posterior for red ball [5]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q1b/)
3. [Q1(c) Fuzzy union, intersection and complements [5]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q1c/)
4. [Q1(d) Irreducibility and stationary distribution [5]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q1d/)
5. [Q2(a) GMM modified log likelihood and parameters [10]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q2a/)
6. [Q2(b) Fuzzy washing-machine controller [10]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q2b/)
7. [Q3(a) Fuzzy relation and max-product comparison [10]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q3a/)
8. [Q3(b) PSO maximization, supplied parameters [10]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q3b/)
9. [Q4(a) Naive Bayes and Laplace smoothing [10]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q4a/)
10. [Q4(b) Transition matrix properties and two-step probabilities [10]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q4b/)
11. [Q5(a) GA selection, crossover and survivor replacement [10]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q5a/)
12. [Q5(b) Mean of maxima and centroid of trapezoids [10]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q5b/)
13. [Q6(a) Genetic algorithm for four-city TSP [10]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q6a/)
14. [Q6(b) Markov process and homework transition paths [10]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q6b/)
15. [Q7(a) Expectation Maximization algorithm [5]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q7a/)
16. [Q7(b) Lambda-cut of a fuzzy relation [5]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q7b/)
17. [Q7(c) ACO path length and pheromone update [5]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q7c/)
18. [Q7(d) Bellman equation [5]](https://deep-learning-study-room.vercel.app/read/is2/tee/papers/paper-2024-reexam--q7d/)