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Implementation of Case-Based Reasoning System For Abalone

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dc.contributor.author Ko, Lei Mon
dc.date.accessioned 2019-08-05T14:43:11Z
dc.date.available 2019-08-05T14:43:11Z
dc.date.issued 2009-12-30
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1801
dc.description.abstract CBR (Case Based Reasoning) is an Artificial Intelligence methodology that provides the foundations for technology of intelligent systems. CBR receives increasing attention within the AI community.CBR is an analogical reasoning method providing both a methodology for problem solving and a cognitive model of people.Case-based reasoning is a recent approach to problem solving and learning that has got a lot of attention over the last few years. A new problem is solved by finding a similar past case, and reusing it in the new problem situation. The basic idea o f CBR is similar problem have similar solutions. The initial purpose of our system is to develop a case-based system where a new case could be quickly compared to the numerous cases in the databases. In our system. we provide the Abalone (sea ear) datasets to implement the system. If the user enters the attributes of abalone ,the system will display the rings of abalone. By adding 1.5 to the result ,the user will get the age of abalone. The system uses nearest-neighbor approach for case retrieval.ID3 algorithm is used in case adaptation. en_US
dc.language.iso en en_US
dc.publisher Fourth Local Conference on Parallel and Soft Computing en_US
dc.title Implementation of Case-Based Reasoning System For Abalone en_US
dc.type Article en_US

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