FUZZY SYSTEMS

Project 1: Computational Intelligence Methods

i) Artificial Neural Networks, Genetic Algorithms, and Fuzzy Systems are methods which enable the development of Computational Intelligent Systems. Each of these methods is based on a human characteristic(s), maybe different one for each method, which justifiably lays the foundation of the method. (Hint- for the artificial neural networks method the characteristic is the biological neuron of the brain).

For each method identify this human-driven characteristic, elaborate and explain its use for developing a computational intelligence system.
Can the above methods be combined to solve problems?
Can the above methods be combined to develop more advanced computational intelligent systems?
Are you aware of any other computational intelligent systems?
ii) Describe the process that has been followed to implement a Multi-layer Perceptron for handwritten digit recognition as presented in the lecture (the code is included in the accompanying Jupyter Notebook ipynb file). Experiment by changing the network’s architecture (number of neurons in hidden layer and number of hidden layers) and comment on how the accuracy of the network is affected by these changes.

Expected length: 20 pages (including figures)

handwritten_digits_sklearn.html handwritten_digits_sklearn.html30

handwritten_digits_sklearn.ipynb handwritten_digits_sklearn.ipynb

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