Fiber Bragg Grating based an Optimal OADM for Performance Enhancement in DWDM using Artificial Neural Network

Fiber Bragg Grating ◽

Performance Enhancement ◽

Bragg Grating ◽

Condition Monitoring System of Electromechanical Equipment Based on Fiber Bragg Grating Sensors and Artificial Neural Network

2018 IEEE 18th International Conference on Communication Technology (ICCT) ◽

10.1109/icct.2018.8599948 ◽

2018 ◽

Author(s):

Xinyue Chen

Keyword(s):

Neural Network ◽

Fiber Bragg Grating ◽

Monitoring System ◽

Condition Monitoring ◽

Bragg Grating ◽

Fiber Bragg Grating Sensors ◽

Artificial Neural ◽

Condition Monitoring System ◽

Electromechanical Equipment

2017 SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference (IMOC) ◽

Fiber Bragg grating interrogation using FBG filters and artificial neural network

10.1109/imoc.2017.8121151 ◽

2017 ◽

Cited By ~ 2

Author(s):

Marco Aurelio Juca ◽

Alexandre Bessa dos Santos

Keyword(s):

Neural Network ◽

Fiber Bragg Grating ◽

Bragg Grating ◽

Simultaneous Measurement of Strain and Temperature with Fiber Bragg Grating Sensor Based on Artificial Neural Network

Laser & Optoelectronics Progress ◽

10.3788/lop47.062801 ◽

2010 ◽

Vol 47 (6) ◽

pp. 062801

Author(s):

李靖 Li Jing ◽

刘微 Liu Wei ◽

刘佳 Liu Jia ◽

赵玉菊李靖刘微刘佳 Zhao Yuju

Keyword(s):

Neural Network ◽

Fiber Bragg Grating ◽

Simultaneous Measurement ◽

Fiber Bragg Grating Sensor ◽

Bragg Grating ◽

Artificial Neural ◽

Bragg Grating Sensor

Artificial Neural Networks and Statistical Pattern Recognition - Old and New Connections - Machine Intelligence and Pattern Recognition ◽

Decision tree performance enhancement using an artificial neural network implementation1 1This work was supported in part by NSF grant IRI-9002087

10.1016/b978-0-444-88740-5.50010-4 ◽

1991 ◽

pp. 71-88 ◽

Cited By ~ 11

Author(s):

Ishwar K. Sethi

Keyword(s):

Neural Network ◽

Decision Tree ◽

Performance Enhancement ◽

Artificial Neural ◽

Tree Performance

Timescale Ensemble Performance Enhancement through use of Artificial Neural Network

INCOSE International Symposium ◽

10.1002/j.2334-5837.2019.00701.x ◽

2019 ◽

Vol 29 (S1) ◽

pp. 478-488

Author(s):

Shikha Maharana ◽

Aakanksha Avnish Bhardwajan ◽

T Subramanya Ganesh ◽

B N Ramakrishna

Keyword(s):

Neural Network ◽

Performance Enhancement ◽

Ensemble Performance ◽

Author response for "Performance enhancement of the artificial neural network–based reinforcement learning for wind turbine yaw control"

10.1002/we.2451/v2/response1 ◽

2019 ◽

Author(s):

Aitor Saenz‐Aguirre ◽

Ekaitz Zulueta ◽

Unai Fernandez‐Gamiz ◽

Alain Ulazia ◽

Daniel Teso‐Fz‐Betono

Keyword(s):

Neural Network ◽

Reinforcement Learning ◽

Wind Turbine ◽

Performance Enhancement ◽

Author Response ◽

Yaw Control ◽

Decision letter for "Performance enhancement of the artificial neural network–based reinforcement learning for wind turbine yaw control"

10.1002/we.2451/v1/decision1 ◽

2019 ◽

Keyword(s):

Neural Network ◽

Reinforcement Learning ◽

Wind Turbine ◽

Performance Enhancement ◽

Yaw Control ◽

Review for "Performance enhancement of the artificial neural network–based reinforcement learning for wind turbine yaw control"

10.1002/we.2451/v2/review2 ◽

2019 ◽

Author(s):

Francesco Castellani

Keyword(s):

Neural Network ◽

Reinforcement Learning ◽

Wind Turbine ◽

Performance Enhancement ◽

Yaw Control ◽

Review for "Performance enhancement of the artificial neural network–based reinforcement learning for wind turbine yaw control"

10.1002/we.2451/v2/review1 ◽

2019 ◽

Keyword(s):

Neural Network ◽

Reinforcement Learning ◽

Wind Turbine ◽

Performance Enhancement ◽

Yaw Control ◽

Performance Enhancement of Wind Farms Using Tuned SSSC Based on Artificial Neural Network

International Journal of Interactive Multimedia and Artificial Intelligence ◽

10.9781/ijimai.2019.05.001 ◽

2019 ◽

Vol 5 (7) ◽

pp. 118 ◽

Cited By ~ 5

Author(s):

Yousry Ibrahim ◽

Salah Kamel ◽

Ahmed Rashad ◽

Loai Nasrat ◽

Francisco Jurado

Keyword(s):

Neural Network ◽

Performance Enhancement ◽

Wind Farms ◽