S. Khasnabis

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This paper presents the results ofa feasibility study on the application ofmachine learning to knowledge acquisition in transponation engineering. An eight-stage knowledge acquisition process is proposed and its individual stages justified and described. Machine learning is used 10 learn about urban rail control. The dewlopment of the representation space(More)
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