AL-504 (C) RGPV B.Tech
Computational Intelligence (CI)
The official syllabus is free to read, no account needed.
Syllabus, notes and important questions for AL-504 (C)
- Syllabus Official RGPV syllabus Free
- Notes 5 documents Free
- Previous Year Papers None for AL-504 (C) yet
- Important Questions None for AL-504 (C) yet
Syllabus units
Topics as the official RGPV syllabus lists them.
Unit 1 Introduction to Computational Intelligence (CI) 9 topics
- Basics of Computational Intelligence (CI)
- History of CI
- Adaptation and Learning
- Self‑Organization
- State‑space search and Evolution
- CI and Soft Computing
- CI techniques and applications
- Decision Trees: introduction, evaluation, splitting criteria, implementation
- Neural Networks: introduction, types, issues, implementation, applications
Unit 2 Fuzzy Set Theory 10 topics
- Fuzzy Sets and characteristics
- Definitions and terminology of fuzzy sets
- Fuzzy operators and relations/composition
- Membership function formulation
- Fuzzy rules and reasoning
- Fuzzy inference systems and input‑space partitioning
- Defuzzification methods
- Fuzzy controllers
- Mamdani, Sugeno, Tsukamoto fuzzy models
- Neuro‑fuzzy modeling and neuro‑fuzzy control
Unit 3 Rough Set Theory 8 topics
- Rough set fundamentals and knowledge representation
- Set approximations, accuracy, vagueness, and uncertainty
- Rough membership function
- Attribute dependency and reduction
- Applications of rough sets
- Hidden Markov Models (HMM)
- Graphical models, variable elimination, belief propagation
- Markov Decision Processes
Unit 4 Evolutionary Computation 5 topics
- Genetic Algorithms: basic genetics, concepts, working principle
- Chromosome encoding, fitness functions, selection methods
- Genetic operators: reproduction, crossover, mutation
- Genetic modeling and problem solving
- Genetic programming, evolutionary programming, evolutionary strategies
Unit 5 Swarm Intelligence 7 topics
- Swarm Intelligence fundamentals
- Ant Colony Optimization (ACO): overview and algorithm
- Particle Swarm Optimization (PSO): basics, social network structure, parameters, algorithm
- Grey Wolf Optimization (GWO)
- Bee Colony Optimization
- Hybrid CI techniques and applications
- CI tools
Exam insights
Counted from 3 past AL-504 (C) papers.
Marks asked per paper, by unit
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Unit 1 Introduction to Computational Intelligence (CI) 103 marks
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Unit 2 Fuzzy Set Theory 2 marks
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Unit 3 Rough Set Theory 14 marks
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Unit 4 Evolutionary Computation 2 marks
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Unit 5 Swarm Intelligence 0 marks
Average marks of the questions from each unit in one paper. You answer only some of them, so the total is more than the paper’s maximum.
Asked again and again
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Explain the challenges of natural language processing.
Asked 2 times: 2022, 2023
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Describe the minimum edit distance algorithm.
Asked 2 times: 2022, 2023
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Explain the role of regular expressions in NLP.
Asked 2 times: 2022, 2023