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Integrating the key approaches of neural networks

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dc.contributor.advisor Wolvaardt, D. E. (Dirkie Elizabeth), 1945- Howard, Beverley Robin 2015-01-23T04:24:48Z 2015-01-23T04:24:48Z 1999-12
dc.identifier.citation Howard, Beverley Robin (1999) Integrating the key approaches of neural networks, University of South Africa, Pretoria, <> en
dc.description.abstract The thesis is written in chapter form. Chapter 1 describes some of the history of neural networks and its place in the field of artificial intelligence. It indicates the biological basis from which neural network approximation are made. Chapter 2 describes the properties of neural networks and their uses. It introduces the concepts of training and learning. Chapters 3, 4, 5 and 6 show the perceptron and adaline in feedforward and recurrent networks particular reference is made to regression substitution by "group method data handling. Networks are chosen that explain the application of neural networks in classification, association, optimization and self organization. Chapter 7 addresses the subject of practical inputs to neural networks. Chapter 8 reviews some interesting recent developments. Chapter 9 reviews some ideas on the future technology for neural networks. Chapter 10 gives a listing of some neural network types and their uses. Appendix A gives some of the ideas used in portfolio selection for the Johannesburg Stock Exchange. en
dc.format.extent 1 online resource (189 leaves)
dc.language.iso en en
dc.subject.ddc 006.32
dc.subject.lcsh Neural networks (Computer science) en
dc.subject.lcsh Artificial intelligence en
dc.title Integrating the key approaches of neural networks en
dc.type Dissertation
dc.description.department Computing M. Sc. (Operations Research)

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