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Titlebook: Big Data; 11th CCF Conference, Enhong Chen,Yang Gao,Wanqi Yang Conference proceedings 2023 The Editor(s) (if applicable) and The Author(s),

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21#
發(fā)表于 2025-3-25 03:37:59 | 只看該作者
,A Study of?Electricity Theft Detection Method Based on?Anomaly Transformer,ployment of smart meters has led to the collection of massive amounts of electricity consumption data, which can help identify electricity theft. However, the challenge of detecting electricity theft is heightened by the category imbalance in the electricity consumption data collected. In this study
22#
發(fā)表于 2025-3-25 07:48:53 | 只看該作者
23#
發(fā)表于 2025-3-25 12:57:56 | 只看該作者
24#
發(fā)表于 2025-3-25 18:05:38 | 只看該作者
,A Transfer Learning Enhanced Decomposition-Based Hybrid Framework for?Forecasting Multiple Time-Ser domains such as energy consumption, network traffic, and solar radiation. The framework is compared with the conventional self-built MVMD-hybrid framework in terms of ARIMA model fitting time and normalized root mean square error (NRMSE) for forecasting accuracy. The results demonstrate that the pr
25#
發(fā)表于 2025-3-25 21:44:36 | 只看該作者
26#
發(fā)表于 2025-3-26 02:06:47 | 只看該作者
The Convolutional Neural Network Combing Feature-Aligned and Attention Pyramid for Fine-Grained Viseliability of high-level feature information are maintained. 2) Attention pyramid: pass the detailed information of low-level features in a bottom-up path to enhance the feature representation; 3) ROI feature refinement: dropblock and zoom-in are used for feature refinement to effectively eliminate
27#
發(fā)表于 2025-3-26 04:37:35 | 只看該作者
OCWYOLO: A Road Depression Detection Method,ed attention mechanisms to existing components without increasing the complexity of the model and achieving the goal of improving accuracy. In addition, we conducted a large number of experiments to verify the superiority of our model. We not only compare it on our road depression dataset but also c
28#
發(fā)表于 2025-3-26 09:26:18 | 只看該作者
29#
發(fā)表于 2025-3-26 12:46:00 | 只看該作者
30#
發(fā)表于 2025-3-26 18:41:14 | 只看該作者
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