Subject Syllabus
AL504 (C) - Computational Intelligence
AIML · Semester 5
Course Modules
Learn topic-wise with Hyper AI and revise using mapped PYQs.
Basics of computational intelligenceHistory of computational intelligenceAdaptation, learning, and self-organizationState space search and evolutionComputational intelligence and soft computingComputational intelligence techniquesApplications of computational intelligenceDecision trees: introduction, evaluation, splitting criteria, and implementationNeural networks: introduction, types, issues, implementation, and applications
Fuzzy sets and fuzzy set characteristicsBasic definition and terminologyFuzzy operatorsFuzzy relations and compositionMember function formulationFuzzy rules and fuzzy reasoningExtensionFuzzy inference systemsInput space partitioning and fuzzy modelingFuzziness and defuzzificationFuzzy controllersMamdani, Sugeno, and Tsukamoto fuzzy modelsNeuro-fuzzy modelingIntroduction to neuro-fuzzy control
Introduction and fundamental conceptsKnowledge representationSet approximations and accuracyVagueness and uncertainty in rough setsRough membership functionAttribute dependency and reductionApplication domainHidden Markov model (HMM)Graphical modelsVariable eliminationBelief propagationMarkov decision processes
Genetic algorithms: basic genetics, concepts, and working principleCreation of offspringEncodingFitness functionSelection functionsGenetic operators: reproduction, crossover, and mutationGenetic modeling, benefits, and problem solvingIntroduction to genetic programming, evolutionary programming, and evolutionary strategies
Introduction to swarm intelligenceAnt colony optimization (ACO): overview and algorithmParticle swarm optimization (PSO): basics, social network structures, parameters, and algorithmGrey wolf optimization (GWO)Application domain of ACO and PSOBee colony optimizationHybrid computational intelligence techniques and applicationsComputational intelligence tools