Modeling and implementation of nonlinear boost converter using local feedback deep recurrent neural network for voltage balancing in energy harvesting applications

2021 ◽  
Author(s):  
Mostafa Noohi ◽  
Ali Mirvakili ◽  
Sayed Alireza Sadrossadat
Keyword(s):  
Neural Network ◽  
Energy Harvesting ◽  
Recurrent Neural Network ◽  
Boost Converter ◽  
Voltage Balancing ◽  
Deep Recurrent Neural Network ◽  
Local Feedback

Jaya Ant Lion Optimization-Driven Deep Recurrent Neural Network for Cancer Classification Using Gene Expression Data (Preprint)

2020 ◽  
Author(s):  
Ramachandro Majji
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Early Stage ◽  
Data Transformation ◽  
Cancer Classification ◽  
Data Normalization ◽  
Ant Lion Optimization ◽  
Deep Recurrent Neural Network ◽  
Novel Strategy ◽  
Feature Dimension

BACKGROUND Cancer is one of the deadly diseases prevailing worldwide and the patients with cancer are rescued only when the cancer is detected at the very early stage. Early detection of cancer is essential as, in the final stage, the chance of survival is limited. The symptoms of cancers are rigorous and therefore, all the symptoms should be studied properly before the diagnosis. OBJECTIVE Propose an automatic prediction system for classifying cancer to malignant or benign. METHODS This paper introduces the novel strategy based on the JayaAnt lion optimization-based Deep recurrent neural network (JayaALO-based DeepRNN) for cancer classification. The steps followed in the developed model are data normalization, data transformation, feature dimension detection, and classification. The first step is the data normalization. The goal of data normalization is to eliminate data redundancy and to mitigate the storage of objects in a relational database that maintains the same information in several places. After that, the data transformation is carried out based on log transformation that generates the patterns using more interpretable and helps fulfill the supposition, and to reduce skew. Also, the non-negative matrix factorization is employed for reducing the feature dimension. Finally, the proposed JayaALO-based DeepRNN method effectively classifies cancer-based on the reduced dimension features to produce a satisfactory result. RESULTS The proposed JayaALO-based DeepRNN showed improved results with maximal accuracy of 95.97%, the maximal sensitivity of 95.95%, and the maximal specificity of 96.96%. CONCLUSIONS The resulted output of the proposed JayaALO-based DeepRNN is used for cancer classification.

scholarly journals Comparison of effects on subjective intelligibility and quality of speech in babble for two algorithms: A deep recurrent neural network and spectral subtraction

2019 ◽  
Vol 145 (3) ◽  
pp. 1493-1503 ◽  
Author(s):  
Mahmoud Keshavarzi ◽  
Tobias Goehring ◽  
Richard E. Turner ◽  
Brian C. J. Moore
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Spectral Subtraction ◽  
Deep Recurrent Neural Network

scholarly journals Latent representation of the human pan-celltype epigenome through a deep recurrent neural network

2021 ◽  
pp. 1-1
Author(s):  
Kevin Bradley Dsouza ◽  
Adam Yifan Li ◽  
Vijay Bhargava ◽  
Maxwell Wing Libbrecht
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Deep Recurrent Neural Network

Deep Recurrent Neural Network DRNN Model for Real-Time Multistage Pumping Data

2018 ◽  
Author(s):  
Srinath Madasu ◽  
Keshava P. Rangarajan
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Recurrent Neural Network ◽  
Deep Recurrent Neural Network

Assessment of deep recurrent neural network-based strategies for short-term building energy predictions

2019 ◽  
Vol 236 ◽  
pp. 700-710 ◽  
Author(s):  
Cheng Fan ◽  
Jiayuan Wang ◽  
Wenjie Gang ◽  
Shenghan Li
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Building Energy ◽  
Short Term ◽  
Deep Recurrent Neural Network

An efficient strategy for predicting river dissolved oxygen concentration: application of deep recurrent neural network model

2021 ◽  
Vol 193 (12) ◽  
Author(s):  
Salar Valizadeh Moghadam ◽  
Ahmad Sharafati ◽  
Hajar Feizi ◽  
Seyed Mohammad Saeid Marjaie ◽  
Seyed Babak Haji Seyed Asadollah ◽  
...  
Keyword(s):  
Neural Network ◽  
Dissolved Oxygen ◽  
Oxygen Concentration ◽  
Network Model ◽  
Recurrent Neural Network ◽  
Neural Network Model ◽  
Dissolved Oxygen Concentration ◽  
Efficient Strategy ◽  
Deep Recurrent Neural Network
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