{"id":5737,"date":"2020-02-08T07:45:54","date_gmt":"2020-02-08T07:45:54","guid":{"rendered":"https:\/\/www.inspirenignite.com\/up\/introduction-to-soft-computing-ie-3rd-sem-syllabus-for-aktu-b-tech-2019-20-scheme-select-subject-1\/"},"modified":"2020-02-08T07:45:54","modified_gmt":"2020-02-08T07:45:54","slug":"introduction-to-soft-computing-ie-3rd-sem-syllabus-for-aktu-b-tech-2019-20-scheme-select-subject-1","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/up\/introduction-to-soft-computing-ie-3rd-sem-syllabus-for-aktu-b-tech-2019-20-scheme-select-subject-1\/","title":{"rendered":"Introduction To Soft Computing IE 3rd Sem Syllabus for AKTU B.Tech 2019-20 Scheme (Select Subject-1)"},"content":{"rendered":"

Introduction To Soft Computing detail syllabus for Instrumentation Engineering (IE), 2019-20 scheme is taken from AKTU<\/a> official website and presented for AKTU students. The course code (KOE036), and for exam duration, Teaching Hr\/Week, Practical Hr\/Week, Total Marks, internal marks, theory marks, and credits do visit complete sem subjects post given below.<\/p>\n

For all the other ie 3rd sem syllabus for b.tech 2019-20 scheme aktu you can visit IE 3rd Sem syllabus for B.Tech 2019-20 Scheme AKTU Subjects<\/a>. For all the other Select Subject-1 subjects do refer to Select Subject-1<\/a>. The detail syllabus for introduction to soft computing is as follows.<\/p>\n

Unit I<\/h4>\n

Introduction to Soft Computing, ARTIFICIAL NEURAL NETWORKS Basic concepts – Single layer perception – Multilayer Perception – Supervised and Unsupervised learning – Back propagation networks – Kohnen’s self-organizing networks – Hopfield network.\n<\/p>\n

Unit II<\/h4>\n

For complete syllabus, results, class timetable and more kindly download iStudy<\/a>. It is a lightweight, easy to use, no images, no pdfs platform to make student’s life easier.<\/b><\/p>\n

Unit III<\/h4>\n

NEURO – FUZZY MODELING Adaptive networks based Fuzzy interface systems – Classification and Regression Trees – Data clustering algorithms – Rule based structure identification – Neuro-Fuzzy controls – Simulated annealing – Evolutionary computation\n<\/p>\n

Unit IV<\/h4>\n

GENETIC ALGORITHMS Survival of the Fittest – Fitness Computations – Cross over – Mutation – Reproduction – Rank method – Rank space method.\n<\/p>\n

Unit V<\/h4>\n

For complete syllabus, results, class timetable and more kindly download iStudy<\/a>. It is a lightweight, easy to use, no images, no pdfs platform to make student’s life easier.<\/b><\/p>\n

Course Outcomes:<\/h4>\n