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Titlebook: Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing; Simon James Fong,Richard C. Millham

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樓主: 拿著錫
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發(fā)表于 2025-3-28 14:38:18 | 只看該作者
2524-552X e and diversity in terms of approach of many issues in big data and streaming. Some novel approaches of this book are the use of these algorithms to all phases of data management (not just a particular phase su978-981-15-6697-4978-981-15-6695-0Series ISSN 2524-552X Series E-ISSN 2524-5538
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發(fā)表于 2025-3-28 20:40:46 | 只看該作者
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發(fā)表于 2025-3-29 01:59:51 | 只看該作者
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發(fā)表于 2025-3-29 07:03:48 | 只看該作者
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發(fā)表于 2025-3-29 09:32:19 | 只看該作者
Lightweight Classifier-Based Outlier Detection Algorithms from Multivariate Data Stream, or lightweight analysis with sliding window, other than global analysis only.” These three mechanisms are then combined with the existing outlier measurements such as “interquartile, local outlier factor and Mahalanobis distance range.” In this study, the computer simulation experiments show encour
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發(fā)表于 2025-3-29 12:52:05 | 只看該作者
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發(fā)表于 2025-3-29 18:44:19 | 只看該作者
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發(fā)表于 2025-3-29 20:40:40 | 只看該作者
Parameter Tuning onto Recurrent Neural Network and Long Short-Term Memory (RNN-LSTM) Network for Feave little value on output feature set. Deep learning methods have been applied to select relevant features in the classification problem; however, the current approach (i.e., search strategies) to the learning of a parameter can either grow out of bound or shrink (they decay exponentially in the nu
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發(fā)表于 2025-3-30 01:19:47 | 只看該作者
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