A self-learning case and rule-based reasoning algorithm for intelligent technology evaluation and selection [Abstract]

This research programme proposes to fulfill the existing gap in knowledge by providing an experience-oriented decision algorithm to solve technology selection problems based on cases and expert’s experience. The approach adopts historical case-based data to extract rules through the ID3 rule inducti...

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Bibliographic Details
Main Authors: Liam Evans, Niels Lohse, Phil Webb
Format: Default Conference proceeding
Published: 2010
Subjects:
Mechanical engineering not elsewhere classified
Case-based
Rule-based reasoning
Expert system
Technology selection
Experience-oriented problems
Self-learning
Mechanical Engineering not elsewhere classified
Online Access:https://hdl.handle.net/2134/25329
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https://hdl.handle.net/2134/25329

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