利用超网络和可学习内核对不同消费类型的消费者进行能源预测

IF 3.8 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Muhammad Umair Danish, Katarina Grolinger
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引用次数: 0

摘要

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Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types
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来源期刊
IEEE Transactions on Power Delivery
IEEE Transactions on Power Delivery 工程技术-工程:电子与电气
CiteScore
9.00
自引率
13.60%
发文量
513
审稿时长
6 months
期刊介绍: The scope of the Society embraces planning, research, development, design, application, construction, installation and operation of apparatus, equipment, structures, materials and systems for the safe, reliable and economic generation, transmission, distribution, conversion, measurement and control of electric energy. It includes the developing of engineering standards, the providing of information and instruction to the public and to legislators, as well as technical scientific, literary, educational and other activities that contribute to the electric power discipline or utilize the techniques or products within this discipline.
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