Synthesizing Energy Consumption Data Using a Mixture Density Network Integrated with Long Short Term Memory-Reference-Cited by-同舟云学术

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Synthesizing Energy Consumption Data Using a Mixture Density Network Integrated with Long Short Term Memory

Published:2019-04 Issue: Volume: Page:
ISSN:
Container-title:2019 IEEE Green Technologies Conference(GreenTech)
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Author:

Sarochar Jonathan,Acharya Ipsita,Riggs Hugo,Sundararajan Aditya,Wei Longfei,Olowu Temitayo,Sarwat Arif I.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8760354/8767117/08767148.pdf?arnumber=8767148

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Four Parameter Distribution Family for Probabilistic Load Forecasting and Scenario Generation with Mixture Density Networks;2023 IEEE Power & Energy Society General Meeting (PESGM);2023-07-16

2. A Generalized Scheme for Attaining Maximum Power Point Tracking and Voltage Regulation in PV Integrated System;2023 5th International Conference on Energy, Power and Environment: Towards Flexible Green Energy Technologies (ICEPE);2023-06-15

3. Federated-WDCGAN: A federated smart meter data sharing framework for privacy preservation;Applied Energy;2023-03

4. Modeling and Mitigating the Cycle Aging Cost of Vehicle Batteries in Energy Transportation Nexus;IEEE Transactions on Smart Grid;2023

5. Energy data generation with Wasserstein Deep Convolutional Generative Adversarial Networks;Energy;2022-10

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