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检索条件"主题词=deep learning autoencoder"
5 条 记 录,以下是1-10 订阅
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Knowledge Extraction From PV Power Generation With deep learning autoencoder and Clustering-Based Algorithms
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IEEE ACCESS 2023年 11卷 69227-69240页
作者: Miraftabzadeh, Seyed Mahdi Longo, Michela Brenna, Morris Politecn Milan Dept Energy Milan Italy
The unpredictable nature of photovoltaic solar power generation, caused by changing weather conditions, creates challenges for grid operators as they work to balance supply and demand. As solar power continues to beco... 详细信息
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C19-MLE: A Multi-Layer Ensemble deep learning Approach for COVID-19 Detection Using Cough Sounds and X-Ray Imaging
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IEEE ACCESS 2024年 12卷 197151-197167页
作者: Hussain, Shabir Amran, Gehad Abdullah Alabrah, Amerah Alkhalil, Lubna Al-Bakhrani, Ali A. Tsinghua Univ Tsinghua Shenzhen Int Grad Sch Inst Biopharmaceut & Hlth Engn Shenzhen 518055 Peoples R China Dalian Univ Technol Dept Management Sci & Engn Dalian 116024 Peoples R China King Saud Univ Coll Comp & Informat Sci Dept Informat Syst Riyadh 11543 Saudi Arabia Dalian Univ Technol Coll Software Dalian 116042 Peoples R China
The COVID-19 pandemic highlighted the urgent need for rapid and efficient screening methods, leading to a growing demand for alternatives to resource-intensive RT-PCR tests. Among these, intelligent, contact-free auto... 详细信息
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A Data-Ahead PV Output Forecasting Method Based on DAE-LSTM
A Data-Ahead PV Output Forecasting Method Based on DAE-LSTM
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International Conference of Electrical, Electronic and Networked Energy Systems, EENES 2024
作者: Xiang, Chuan Liu, Xiang Yang, Tiankai College Of Marine Electrical Engineering Dalian Maritime University Dalian111600 China
With the increasing penetration of photovoltaic generation (PV), its output has impacted the power grid significantly. However, due to complex weather factors, PV output is intermittent and uncertain, making it challe... 详细信息
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A deep learning Method to Accelerate the Disaster Response Process
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REMOTE SENSING 2020年 第3期12卷 544-544页
作者: Antoniou, Vyron Potsiou, Chryssy Hellen Army Geog Directorate Cholargos 15561 Greece Natl Tech Univ Athens Sch Rural & Surveying Engn Dept Topog Zografos 15780 Greece
This paper presents an end-to-end methodology that can be used in the disaster response process. The core element of the proposed method is a deep learning process which enables a helicopter landing site analysis thro... 详细信息
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Data anomaly detection in photovoltaic power time-series via unsupervised deep learning with insufficient information
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Sustainable Energy, Grids and Networks 2025年 43卷
作者: Seyed Mahdi Miraftabzadeh Michela Longo Sonia Leva Nicoletta Matera Department of Energy Politecnico di Milano Via Lambruschini 4 Milano 20156 Italy
Anomaly detection in photovoltaic (PV) systems is essential to improving reliability, ensuring electricity production and equipment safety, and decreasing their negative impact on the economy of the operation system. ... 详细信息
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