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Titlebook: Intelligent Information Systems; Proceedings of the I Mieczysław Kłopotek,Maciej Michalewicz,Sławomir T. Conference proceedings 2000 Spring

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楼主: Adentitious
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Verification of Rule Knowledge Bases Using Decision Unitsty of expert systems. Verification of knowledge bases has emerged as a significant problem in the development of expert systems. We argue that knowledge bases verification can not be delayed until the final knowledge base realization and we suppose that verification should be performed incrementally
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Artificial Neural Network for Multiprocessor Tasks Schedulinglong, in general, to NP-hard class and it is very likely that no polynomial-time exact algorithm solving them could ever be found. Hence, a dedicated artificial neural network has been proposed as a tool for solving multiprocessor tasks scheduling problems. The paper presents the proposed neural net
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1867-5662 ra, Poland, on June 12-16, 2000. This is ninth, in the order, symposium organized by the Institute of Computer Science of Polish Academy of Sciences and devoted to new trends in (broadly understood) Artificial Intelligence. The idea of organizing such meetings dates back to 1992. Our main in­ tentio
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Generation of Exhaustive Rule Sets Using a Reduct Generating Algorithmvanced algorithms. This paper introduces and experimentally evaluates an algorithm that is based on the notion of the discernibility list and that may be used for generating decision rules as well as attribute reducts. All the results of the experiments reported in this paper have been obtained for real-life data sets.
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Modeling Agent Organizationse designer is to create efficient enterprises producing the desired commodity. The market is modeled as the price oligopoly. The price oligopoly serves to eliminate enterprises that are not efficient.
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Methodology of Diagnostic Knowledge Acquisition from Databases of Examplesdiagnostic knowledge from a set of examples we apply both machine learning and knowledge discovery methods. An example of the application of described methods for the acquisition of knowledge suitable for diagnosing complex technical states of rotating machinery is also given.
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Artificial Neural Network for Multiprocessor Tasks Schedulingartificial neural network has been proposed as a tool for solving multiprocessor tasks scheduling problems. The paper presents the proposed neural network structure and algorithms used to train it. Efficiency of the approach has been evaluated experimentally. Examples and computational experiment results are also shown.
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Optimization and Interpretation of Rule-Based Classifierspretation of relevant rules is possible using (probabilistic) confidence intervals. A real life example of such interpretation is given for personality disorders. The approach to optimization and interpretation described here is applicable to any rule-based system.
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