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Revision Michael J. Watts http://mike.watts.net.nz

Revision Michael J. Watts mike.watts.nz

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Revision Michael J. Watts http://mike.watts.net.nz. Lecture Outline. Overview of course material. Introduction to AI. Artificial / Computational Intelligence CI models. Data Transformation. Statistical operations on Data Data transformations The objectives of a data transform - PowerPoint PPT Presentation

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Page 1: Revision Michael J. Watts mike.watts.nz

Revision

Michael J. Watts 

http://mike.watts.net.nz

Page 2: Revision Michael J. Watts mike.watts.nz

Lecture Outline

• Overview of course material

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Introduction to AI

• Artificial / Computational Intelligence• CI models

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Data Transformation

• Statistical operations on Data• Data transformations

o The objectives of a data transformo Linear versus non-linear transformationso Transformations for pre-processing of datao DFT and FFT Transformationso Wavelet Transformations

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Rule Based Systems

• Production systems• Facts & Templates• Production rules• The inference process• Advantages of production systems• Disadvantages of production systems• Expert systems

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Fuzzy Sets and Fuzzification

• Crisp sets• Fuzzy sets• Fuzzy membership functions• Fuzzification• Fuzzy logic

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Fuzzy Rules, Inference and Defuzzification

• Fuzzy rules• Fuzzy inference• Defuzzification

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Fuzzy Systems

• Fuzzy systems• Developing fuzzy systems• Advantages of fuzzy systems• Disadvantages of fuzzy systems

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Applications of Fuzzy Systems

• Advantages of fuzzy systems• Pattern recognition / Classification• Fuzzy control• Decision making

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Biological and Artificial Neurons

• Biological Neurons• Biological Neural Networks• Artificial Neurons• Artificial Neural Networks

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Perceptrons

• Perceptron architecture• Perceptron learning• Problems with perceptrons

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Multi-Layer Perceptrons

• Multi-Layer Perceptrons• Terminology• Advantages• Problems

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Backpropagation Training

• Backpropagation training• Error calculation• Error surface• Pattern vs. Batch mode training• Restrictions of backprop• Problems with backprop

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Kohonen Self Organising Maps

• Vector Quantisation• Unsupervised learning• Kohonen Self Organising Topological Maps

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Applying Neural Networks

• When to use an ANN• Preparing the data• Apportioning data• What kind of ANN to use• Training ANN

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Evolution

• What is evolution?• What evolution is not• Lamarckian evolution• Mendellian genetics• Darwinian evolution

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Genetic Algorithms

• Genetic algorithms• Jargon• Advantages of GAs• Disadvantages of GAs• Simple genetic algorithm• Encoding schemata• Fitness evaluation

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Genetic Algorithms

• Selection• Creating new solutions• Crossover• Mutation• Replacement strategies• Word matching example

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Evolution StrategiesEvolutionary Programming

Genetic Programming• Evolution Strategies• Evolutionary Programming• Genetic Programming

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Applications of Evolutionary Algorithms

• Advantages of EA• EA Application areas• Scheduling• Load balancing• Engineering• Path Planning

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Evolutionary Algorithms and Neural Networks

• Problems with ANN• EA and ANNs• ANN Topology Selection by EA• Initial Weight Selection• Selecting Control Parameters• EA Training

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Evolutionary Algorithms and Fuzzy Systems

• Advantages of fuzzy systems• Problems with fuzzy systems• Applying EA to fuzzy systems

o Optimisation of MFo Optimisation of ruleso Optimisation of fuzzy systems

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IIS for Speech Processing

• Speech Production• Speech Segments• Speech Data Capture• Representing Speech Data• Speech Processing• Speech Recognition

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IIS for Bioinformatics

• What is bioinformatics?• What is DNA?• How is it processed in cells?• What is DNA data?• How is DNA data represented?• How can IS be applied to DNA data?

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IIS for Finance

• Economic data• Applications• Why is it hard?• Methods to use• Applications of IIS

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IIS for Image Processing

• What are images?• Why process them?• What is Image Processing/Recognition?