Reference no: EM133682612

Intelligent Systems

Answer the following questions on rule based system.
What are forward chaining and back chaining reasoning? Use an example to illustrate the differences between them.
Describe the different ways to resolve conflicting rules.
Explain how to handle uncertainty in rule based system with example.
Answer the following questions on fuzzy system.
Explain the difference between fuzzy logic and probability.
Explain the four operations on fuzzy sets using figures or examples.
Describe the three main components of a fuzzy system.
What is the difference between Mamdani and Sugeno fuzzy inference methods.

This exercise provides an example of how to classify image using a pre-trained deep neural network (deep convolutional neural network GoogLeNet).
After you have completed the tutorial above, answer the following questions.
What is a pre-trained deep neural network?
How can you make used of a pre-trained deep neural network for your own application?
What parameters can be adjusted in the training?

This exercise provides an example of how to use the fuzzy clustering technique. After you have completed the tutorial above, answer the following questions.
What is a clustering? How is clustering different from classification technique?
What is the advantage of using fuzzy clustering vs conventional clustering? Illustrate with example.
What parameters can be adjusted in the learning?

This example provides you with steps on how to build a Neural Network model. After you have completed the tutorial above, answer the following questions.
What is this Neural Network model perform? What are the input and output?
How do you test the accuracies of the model?
If you are to provide the trained Neural Network model for your client to use, how do you save the model so that it can be distribute to the client? Such that the client does not need to train the model again?
What parameters can be adjusted in the learning to optimise the best result?