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- W2893329123 abstract "W288 the development of automation, the dispatching automation system need to handle a large amount of messy signals. It is significant to ensure system stability by recognizing and classifying signals quickly and accurately. This paper introduces a learning algorithm based on the feature weight of CFuzziness function, which could solve dimension disaster problem of fuzzy C mean algorithm. By minimizing the function CFuzziness with the gradient descent algorithm, a proper weight value can be given to each feature, and the weighted fuzzy C mean algorithm is obtained. The results show that the clustering results of weighted fuzzy C mean algorithm are superior to the fuzzy C mean algorithm." @default.
- W2893329123 created "2018-10-05" @default.
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- W2893329123 date "2018-05-01" @default.
- W2893329123 modified "2023-09-25" @default.
- W2893329123 title "Research on Dispatching Automation System Automatic Recognition Technology Based on Fuzzy Pattern Recognition Algorithm" @default.
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- W2893329123 doi "https://doi.org/10.1109/imcec.2018.8469414" @default.
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