期刊名称：Journal of Advances in Information Technology
印刷版ISSN：1798-2340
出版年度：2016
卷号：7
期号：2
页码：105-112
DOI：10.12720/jait.7.2.105-112
出版社：Academy Publisher
摘要：The Case-Based Reasoning (CBR) is a problem solving approach based on reuse by analogy from past experiences. A CBR system is a combination of processes and knowledge called “knowledge containers”, its reasoning power can be improved through the use of domain knowledge. CBR systems combining case specific knowledge with general domain knowledge models are called Knowledge Intensive CBR (KI-CBR). Although CBR claims to reduce the effort required for developing knowledge-based systems substantially compared with more traditional Artificial Intelligence approaches, the implementation of a CBR application from scratch is still a time consuming task. The present work aims to develop a CBR application for fault diagnosis of steam turbines that integrates a domain knowledge modeling in an ontological form and focuses on the similarity-based retrieval step. This system is view as a KI-CBR system based on domain ontology, built around jCOLIBRI and myCBR a well-known frameworks to design KI-CBR systems. During prototyping, we examine the use and functionality of the focused frameworks. A comparative study is performed with results of presenting a successful retrieval task and demonstrating that jCOLIBRI and myCBR are well adapted to design KI-CBR system.
