By Simon Kendal, Malcolm Creen
The authors use a fresh and novel 'workbook' writing variety which provides the ebook a truly sensible and simple to exploit consider. It comprises methodologies for the advance of hybrid details platforms, covers neural networks, case dependent reasoning and genetic algorithms in addition to professional platforms. quite a few tips that could net dependent assets and present learn also are integrated. The content material of the ebook has been effectively utilized by undergraduates worldwide. it really is aimed toward undergraduates and a powerful maths history isn't really required.
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Additional info for An Introduction to Knowledge Engineering
Com/) to create a radial basis network that approximates a function deﬁned by a set of data points. Self-Organising Maps Although there has been considerably more progress in supervised learning research, Tuevo Kohonen has had some success with his development of a selforganising map (SOM). The SOM (also known as the Kohonen feature map) algorithm is one of the best-known ANN algorithms. Self-organising maps are a 46 An Introduction to Knowledge Engineering data visualisation technique that reduces the dimensions of data through the use of self-organising NNs.
2. 3. 4. 5. 6. Expert systems Neural networks (NNs) Case-based reasoning (CBR) Genetic algorithms Intelligent agents Data mining. Objectives By the end of the chapter you will be able to: r describe the characteristics of a knowledge-based system r explain the main elements of knowledge-based systems and how they work r evaluate the advantages and limitations of knowledge-based systems r identify appropriate contexts for the use of particular types of knowledge-based systems. 26 Types of Knowledge-Based Systems 27 SECTION 1: EXPERT SYSTEMS Introduction This section provides you with an introduction to expert systems and their use within knowledge engineering.
Case-based reasoning works in a similar way to which humans select a course of action from experience. 56 An Introduction to Knowledge Engineering New case Retrieve matching Matched cases Learn Case base Adapt? 11. Case-based reasoning process. Typical Problems Handled with CBR Problems handled by the use of CBR tend to be those with a classiﬁcation and diagnosis feature: Observations classification diagnosis repair Domain rules Activity 14 What other examples of classiﬁcation and diagnosis situations can you think of that would beneﬁt from using a CBR approach to problem solving?