B.E. (Artificial Intelligence and Data Science) Neural Networks and Fuzzy Systems Lab Syllabus - Mumbai University
This is the Fourth Year BE AI and DS syllabus under CBCS REV-2019 'C' Scheme, in force from the academic year 2023-24. The University has published no NEP 2020 syllabus for Semesters V to VIII of any engineering branch, so this is the scheme you are examined on — exam form 1T01817 and 1T01818. The first and second years of the degree are on NEP 2020.
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Syllabus for Neural Networks and Fuzzy Systems Lab
Module 1
- Demonstrate Union and intersection of two Fuzzy Sets.
Module 2
- Demonstrate difference between two Fuzzy Sets.
Module 3
- Implement Fuzzy membership functions.
Module 4
- Implement Fuzzy Inference system (FIS).
Module 5
- Implement any De-fuzzification of membership method.
Module 6
- Implement Bidirectional Associative Memory(BAM) Network
Module 7
- Implement Radial basis function network.
Module 8
- Implement Basic Neural Network learning rules.
Module 9
- Implement any Unsupervised Learning algorithm.
Module 10
- Implement Kohonen Self- Organizing Feature Maps
Module 11
- Implement a Probabilistic Neural Network.
Module 12
- Implement any Ensemble neural model.
Module 13
- Design any one Neuro-Fuzzy system.
Useful Links
- 1 https://onlinecourses.nptel.ac.in/noc21_ge07/preview
- 2 http://www.nitttrc.edu.in/nptel/courses/video/127105006/L25.html
- 3 https://archive.nptel.ac.in/courses/108/104/108104157/
Reproduced from the University of Mumbai syllabus for B.E. (Artificial Intelligence and Data Science), item 6.12 (N), under CBCS REV-2019 'C' Scheme, in force from the academic year 2023-24. Wording, module numbering and hours are as printed in that syllabus.
The complete syllabus
This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.