COMPUTATIONAL INTELLIGENCE

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Presentation transcript:

COMPUTATIONAL INTELLIGENCE SOFT COMPUTING & COMPUTATIONAL INTELLIGENCE Biologically inspired computing models Compatible with human expertise/reasoning Intensive numerical computations Data and goal driven Model-free learning Fault tolerant Real world/novel applications RENSSELAER

COMPUTATIONAL INTELLIGENCE SOFT COMPUTING & COMPUTATIONAL INTELLIGENCE Artificial Neural Networks (ANN) Fuzzy Logic Genetic Algorithms (GAs) Fractals/Chaos Artificial life Wavelets Data mining ANNs FL GAs RENSSELAER

Biological neuron signal dendrites flow synapse axon hillock cell body hair cell (sensory transducer) signal flow dendrites synapse axon hillock cell body axon synapse RENSSELAER

 Artificial neuron i1 w1 inputs o output i2 w2 o w3 i3 w1 i1 + w2 i2 sigmoid nonlinear transfer function weighted sum of the inputs w1 i1 + w2 i2 + w3 i3 w1 i1 + w2 i2 + w3 i3 RENSSELAER

Neural net yields weights to map inputs to outputs  Neural Network Molecular weight w11 h w11   Boiling Point H-bonding   Biological response Hydrofobicity  h Electrostatic interactions w23  w34 Observable Projection Molecular Descriptor There are many algorithms that can determine the weights for ANNs RENSSELAER

Neural networks in a nutshell A problem can be formulated and represented as a mapping problem from Such a map can be realized by an ANN, which is a framework of basic building blocks of McCulloch-Pitts neurons The neural net can be trained to conform with the map based on samples of the map and will reasonably generalize to new cases it has not encountered before RENSSELAER

Neural network as a map RENSSELAER

McCulloch-Pitts Neuron y x 1 3 N S f() w 2 RENSSELAER

Neural network as collection of M-P neurons x 1 2 w 11 12 13 23 22 32 21 3 y First hidden layer Second hidden Output neuron RENSSELAER

Kohonen SOM for text retrieval on WWW newsgroups WEBSOM node u21 Click arrows to move to neighboring nodes on the map. Instructions Re: Fuzzy Neural Net References Needed Derek Long , 27 Oct 1995, Lines: 24. Distributed Neural Processing Jon Mark Twomey, 28 Oct 1995, Lines: 12. Re: neural-fuzzy TiedNBound, 11 Dec 1995, Lines: 10. New neural net C library available Simon Levy, 2 Feb 1996, Lines: 15. Re: New neural net C library available Michael Glover, Sun, 04 Feb 1996, Lines: 25.

From Guido De Boeck SOM’s for Data Mining To be published (Springer Verlag)