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Titlebook: Smart Meter Data Analytics; Electricity Consumer Yi Wang,Qixin Chen,Chongqing Kang Book 2020 Science Press and Springer Nature Singapore Pt

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樓主: Magnanimous
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發(fā)表于 2025-3-28 16:27:18 | 只看該作者
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發(fā)表于 2025-3-29 14:12:19 | 只看該作者
Probabilistic Residential Load Forecasting,sed point forecasting is extended to probabilistic forecasting in the form of quantiles. Numerical experiments are conducted on an open dataset from Ireland. Forecasting for both residential and commercial consumers is tested. Results show that the proposed method has superior performance over traditional methods.
47#
發(fā)表于 2025-3-29 17:09:03 | 只看該作者
Socio-demographic Information Identification,rehensive comparisons with state-of-the-art and advanced machine learning techniques are conducted. Case studies on an Irish dataset demonstrate the effectiveness of the proposed deep CNN-based method, which achieves higher accuracy in identifying the socio-demographic information about the consumers.
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發(fā)表于 2025-3-29 23:24:57 | 只看該作者
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發(fā)表于 2025-3-30 03:33:25 | 只看該作者
engineers.Low Power Design Essentials contains all the topics of importance to the low power designer. The book lays the foundation with background chapters entitled “Advanced MOS Transistors and Their Models” and “Power Basics”. These chapters are followed by chapters on the design process includi
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發(fā)表于 2025-3-30 05:11:47 | 只看該作者
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