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- W2662520699 abstract "Abstract Machine learning can be used in the acquisition of knowledge for an operator assistant system. In applications such as fault diagnosis, the order of occurrence of events may be important. In actual systems, noise is also present. Machine learning algorithms for diagnostic knowledge should be capable of inducing knowledge reliably froIn noisy input, taking the sequence of events into account. This paper presents a method, based on genetic learning, which may be applied to the acquisition of a knowledge base for fault diagnosis. The algorithm is evaluated using a distribu tion system fault simulator." @default.
- W2662520699 created "2017-06-30" @default.
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- W2662520699 date "1993-07-01" @default.
- W2662520699 modified "2023-09-26" @default.
- W2662520699 title "Machine Learning of Diagnostic Knowledge for a Power Distribution Fault Diagnostician using a Genetic Algorithm" @default.
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- W2662520699 doi "https://doi.org/10.1016/s1474-6670(17)48581-8" @default.
- W2662520699 hasPublicationYear "1993" @default.
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