Improved Electromagnetic Signal Power Loss Prediction Using Fused Adaptive Linear Based Smoothing Technique

IMPROVED ADAPTIVE SIGNAL POWER LOSS PREDICTION USING COMBINED VECTOR STATISTICS BASED SMOOTHING AND NEURAL NETWORK APPROACH

Progress In Electromagnetics Research C ◽

10.2528/pierc18011203 ◽

2018 ◽

Vol 82 ◽

pp. 155-169 ◽

Cited By ~ 3

Author(s):

Virginia Chika Ebhota ◽

Joseph Isabona ◽

Viranjay M. Srivastava

Keyword(s):

Neural Network ◽

Power Loss ◽

Signal Power ◽

Network Approach ◽

Neural Network Approach ◽

Loss Prediction ◽

Adaptive Signal

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Investigation and Comparison of Generalization Ability of Multi-Layer Perceptron and Radial Basis Function Artificial Neural Networks for Signal Power Loss Prediction

International Journal on Communications Antenna and Propagation (IRECAP) ◽

10.15866/irecap.v9i1.15330 ◽

2019 ◽

Vol 9 (1) ◽

pp. 46

Author(s):

Virginia C. Ebhota ◽

Joseph Isabona ◽

Viranjay M. Srivastava

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Radial Basis Function ◽

Basis Function ◽

Power Loss ◽

Signal Power ◽

Multi Layer Perceptron ◽

Generalization Ability ◽

Loss Prediction ◽

Artificial Neural

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Signal power loss prediction based on artificial neural networks in microcell environment

2017 IEEE 3rd International Conference on Electro-Technology for National Development (NIGERCON) ◽

10.1109/nigercon.2017.8281897 ◽

2017 ◽

Author(s):

Virginia Chika Ebhota ◽

Joseph Isabona ◽

Viranjay M. Srivastava

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Power Loss ◽

Signal Power ◽

Loss Prediction ◽

Artificial Neural

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Performance Analysis of Learning Rate Parameter on Prediction of Signal Power Loss for Network Optimization and Better Generalization

Wireless Personal Communications ◽

10.1007/s11277-020-08061-z ◽

2021 ◽

Author(s):

Virginia C. Ebhota ◽

Viranjay M. Srivastava

Keyword(s):

Performance Analysis ◽

Network Optimization ◽

Power Loss ◽

Learning Rate ◽

Signal Power ◽

Rate Parameter

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Model-based aging tolerant control with power loss prediction of Proton Exchange Membrane Fuel Cell

International Journal of Hydrogen Energy ◽

10.1016/j.ijhydene.2018.11.219 ◽

2020 ◽

Vol 45 (19) ◽

pp. 11242-11254 ◽

Cited By ~ 2

Author(s):

Mathieu Bressel ◽

Mickael Hilairet ◽

Daniel Hissel ◽

Belkacem Ould Bouamama

Keyword(s):

Fuel Cell ◽

Power Loss ◽

Proton Exchange Membrane ◽

Proton Exchange ◽

Model Based ◽

Loss Prediction ◽

Exchange Membrane

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Power Loss Prediction and Precise Modeling of Magnetic Powder Components in DC–DC Power Converter Application

IEEE Transactions on Power Electronics ◽

10.1109/tpel.2014.2330952 ◽

2015 ◽

Vol 30 (4) ◽

pp. 2232-2238 ◽

Cited By ~ 16

Author(s):

Alaa Hilal ◽

Marie-Ange Raulet ◽

Christian Martin ◽

Fabien Sixdenier

Keyword(s):

Power Loss ◽

Power Converter ◽

Magnetic Powder ◽

Dc Power ◽

Loss Prediction

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Prediction of Signal Power Loss (at Micro-Cell Environments) Using Generalized Adaptive Regression and Radial Basis Function ANN Models Built on Filter for Error Correction

International Journal on Communications Antenna and Propagation (IRECAP) ◽

10.15866/irecap.v11i2.19964 ◽

2021 ◽

Vol 11 (2) ◽

pp. 94

Author(s):

Virginia C. Ebhota ◽

Viranjay M. Srivastava

Keyword(s):

Radial Basis Function ◽

Error Correction ◽

Basis Function ◽

Power Loss ◽

Signal Power ◽

Radial Basis ◽

Adaptive Regression ◽

Ann Models

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Structure Based Compact Model for Output Capacitance of Trench Field-Plate MOSFET to Enable Power Loss Prediction

10.7567/ssdm.2017.o-4-02 ◽

2017 ◽

Author(s):

K. Kobayashi ◽

M. Sudo ◽

I. Omura

Keyword(s):

Power Loss ◽

Compact Model ◽

Field Plate ◽

Loss Prediction ◽

Output Capacitance

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DeepSolarEye: Power Loss Prediction and Weakly Supervised Soiling Localization via Fully Convolutional Networks for Solar Panels

2018 IEEE Winter Conference on Applications of Computer Vision (WACV) ◽

10.1109/wacv.2018.00043 ◽

2018 ◽

Cited By ~ 14

Author(s):

Sachin Mehta ◽

Amar P. Azad ◽

Saneem A. Chemmengath ◽

Vikas Raykar ◽

Shivkumar Kalyanaraman

Keyword(s):

Power Loss ◽

Solar Panels ◽

Convolutional Networks ◽

Fully Convolutional Networks ◽

Loss Prediction ◽

Weakly Supervised

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Model Predictive Control Based Dynamic Power Loss Prediction for Hybrid Energy Storage System in DC Microgrids

IEEE Transactions on Industrial Electronics ◽

10.1109/tie.2021.3108701 ◽

2021 ◽

pp. 1-1

Author(s):

Xibeng Zhang ◽

Benfei Wang ◽

Don Gamage ◽

Abhisek Ukil

Keyword(s):

Energy Storage ◽

Predictive Control ◽

Power Loss ◽

Storage System ◽

Energy Storage System ◽

Dc Microgrids ◽

Hybrid Energy ◽

Hybrid Energy Storage ◽

Hybrid Energy Storage System ◽

Loss Prediction

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