Vang Randy creator Ramakoti Sadananda Chairperson Yulu, Qi Examination committee Shrestha, Surendra Man Examination committee New Zealand Scholarship donor text th Bangkok Asian Institute of Technology 1996 monographic eng

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79 leaves : ill. Artificial Neural Networks are new technologies for classifications. They are able to process incomplete and imprecise data and to detect non-linear relations in the data. Artificial learning algorithms can be subdivided into two types, supervised and unsupervised. Neural networks learn in massively parallel and self-organizing way. Unsupervised learning neural networks, like Kohonen's self-organizing feature maps (Kohonen, 1989), learn the structure of high-dimensional data by mapping it on low-dimensional topologies, preserving the distribution and topology of the data. In this thesis the Kohonen self-organizing feature map is applied to classification of a land cover data set. The data was collected from existing database of land cover regions in Cambodia that were · expertly labeled into many classes. Rule extraction extracts land cover classes produced by self-organizing methods for the queries of knowledge. However, a rule generation algorithm of rule extraction out of the neural network, which could be used by the geological expert. A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering. Thesis (M.Eng.) - Asian Institute of Technology, 1996 Neural networks (Computer science) Asian Institute of Technology. http://203.159.5.9/ait-thesis/detail.php?q=B14576 http://203.159.5.9/ait-thesis/detail.php?q=B14576 080998 20260818144950.0