Solar PV Power Prediction Using A New Approach Based on Hybrid Deep Neural Network

2019 ◽  
Author(s):  
Dan A. Rosa de Jesus ◽  
Paras Mandal ◽  
Shantanu Chakraborty ◽  
Tomonobu Senjyu
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Solar Pv ◽  
Power Prediction ◽  
New Approach

scholarly journals Deep neural network for orthogonal frequency division multiplexing systems without cyclic prefix transmission

2018 ◽  
Vol 189 ◽  
pp. 04016
Author(s):  
Viet-Hung Nguyen ◽  
Minh-Tuan Nguyen ◽  
Yong-Hwa Kim
Keyword(s):  
Neural Network ◽  
Orthogonal Frequency Division Multiplexing ◽  
Deep Neural Network ◽  
Cyclic Prefix ◽  
Wireless Transmission ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Ofdm System ◽  
New Approach ◽  
Multiplexing Systems

Orthogonal frequency division multiplexing (OFDM) is widely used in wired or wireless transmission systems. In the structure of OFDM, a cycle prefix (CP) has been exploited to avoid the effects of inter-symbol interference (ISI) and inter-carrier interference (ICI). This paper proposes a new approach to transmit the signals without CP transmission. Using the deep neural network, the proposed OFDM system transmits data without the CP. Simulation results show that the proposed scheme can estimate the CP at the receiver and overcome the effect of ISI.

Solar PV Power Forecasting Approach Based on Hybrid Deep Neural Network

2021 ◽  
pp. 125-133
Author(s):  
Kuo-Chi Chang ◽  
Abdalaziz Altayeb Ibrahim Omer ◽  
Kai-Chun Chu ◽  
Fu-Hsiang Chang ◽  
Hsiao-Chuan Wang ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Solar Pv ◽  
Power Forecasting

Data Fusion Based Hybrid Deep Neural Network Method for Solar PV Power Forecasting

2019 ◽  
Author(s):  
Dan A. Rosa De Jesus ◽  
Paras Mandal ◽  
Miguel Velez-Reyes ◽  
Shantanu Chakraborty ◽  
Tomonobu Senjyu
Keyword(s):  
Neural Network ◽  
Data Fusion ◽  
Deep Neural Network ◽  
Solar Pv ◽  
Neural Network Method ◽  
Network Method ◽  
Power Forecasting

Wind power prediction using deep neural network based meta regression and transfer learning

2017 ◽  
Vol 58 ◽  
pp. 742-755 ◽  
Author(s):  
Aqsa Saeed Qureshi ◽  
Asifullah Khan ◽  
Aneela Zameer ◽  
Anila Usman
Keyword(s):  
Neural Network ◽  
Wind Power ◽  
Transfer Learning ◽  
Deep Neural Network ◽  
Power Prediction ◽  
Wind Power Prediction ◽  
Meta Regression

scholarly journals Specular Reflections Detection and Removal Based on Deep Neural Network for Endoscope Images

2021 ◽  
Author(s):  
Tianyu Liu ◽  
chongyu wang ◽  
Junyu Chang ◽  
Liangjing Yang
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Specular Reflection ◽  
New Approach ◽  
Learning Framework ◽  
Specular Reflections ◽  
Clinical Purpose ◽  
Novel Model ◽  
Opening Up ◽  
Surgical Videos

Specular reflections have always been undesirable when processing endoscope vision for clinical purpose. Scene afflicted with strong specular reflection could result in visual confusion for the operation of surgical robot. In this paper, we propose a novel model based on deep learning framework, known as Surgical Fix Deep Neural Network (SFDNN). This model can effectively detect and fix the reflection points in different surgical videos hence opening up a whole new approach in handling undesirable specular reflections.

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