Determination of flutter derivatives via a neural network approach

Journal of Sound and Vibration ◽

10.1016/s0022-460x(02)01279-8 ◽

2003 ◽

Vol 263 (4) ◽

pp. 797-813 ◽

Author(s):

C.H. Chen

Keyword(s):

Neural Network ◽

Network Approach ◽

Neural Network Approach ◽

Flutter Derivatives

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Accurate determination of natural gas compressibility factor by measuring temperature, pressure and Joule-Thomson coefficient: Artificial neural network approach

Journal of Petroleum Science and Engineering ◽

10.1016/j.petrol.2021.108427 ◽

2021 ◽

pp. 108427

Author(s):

Mahmood Farzaneh-Gord ◽

Hamid Reza Rahbari ◽

Behnam Mohseni-Gharesafa ◽

Alexander Toikka ◽

Irina Zvereva

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Accurate Determination ◽

Compressibility Factor ◽

Network Approach ◽

Neural Network Approach ◽

Thomson Coefficient ◽

Gas Compressibility ◽

Artificial Neural Network Approach

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Determination of the Geoacoustical Parameters of a Sedimentary Layer from Surface Acoustic Waves: A Neural Network Approach

Full Field Inversion Methods in Ocean and Seismo-Acoustics - Modern Approaches in Geophysics ◽

10.1007/978-94-015-8476-0_28 ◽

1995 ◽

pp. 171-176 ◽

Author(s):

J. Guilbot ◽

F. Magand

Keyword(s):

Neural Network ◽

Acoustic Waves ◽

Surface Acoustic Waves ◽

Network Approach ◽

Neural Network Approach ◽

Sedimentary Layer

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Determination of Horizontal Permeability Through a Probability Neural Network Approach

10.2118/36266-ms ◽

1996 ◽

Author(s):

L. Soares ◽

T. Ribeiro ◽

F. Alves ◽

M.J. Pereira

Keyword(s):

Neural Network ◽

Network Approach ◽

Neural Network Approach ◽

Probability Neural Network ◽

Horizontal Permeability

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Deep Convolutional Neural Network Approach as a Universal Tool for Determination of Local 3D Structure from ABF STEM Images of Perovskitesy

Microscopy and Microanalysis ◽

10.1017/s1431927618003148 ◽

2018 ◽

Vol 24 (S1) ◽

pp. 530-531

Author(s):

Nouamane Laanait ◽

Albina Y. Borisevich

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

3D Structure ◽

Deep Convolutional Neural Network ◽

Network Approach ◽

Neural Network Approach

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Determination of particle trajectories in an isolated conductor GIB using neural network approach

2003 Annual Report Conference on Electrical Insulation and Dielectric Phenomena ◽

10.1109/ceidp.2003.1254902 ◽

2004 ◽

Author(s):

P. Upadhyay ◽

J. Amarnath ◽

B.P. Singh ◽

K.D. Shrivastava ◽

P. Upadhyay

Keyword(s):

Neural Network ◽

Network Approach ◽

Particle Trajectories ◽

Neural Network Approach

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Determination of Optimum Body Diameter of Air Cyclones Using a New Empirical Model and a Neural Network Approach

Environmental Engineering Science ◽

10.1089/ees.2006.23.680 ◽

2006 ◽

Vol 23 (4) ◽

pp. 680-690 ◽

Author(s):

Kaan Yetilmezsoy

Keyword(s):

Neural Network ◽

Empirical Model ◽

Network Approach ◽

Neural Network Approach ◽

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A neural network approach for wind retrieval from the ERS-1 scatterometer data. 1. Determination of the geophysical model function of ERS-1 scatterometer

Proceedings of OCEANS'94 ◽

10.1109/oceans.1994.363918 ◽

2002 ◽

Author(s):

C. Mejia ◽

S. Thiria ◽

M. Crepon ◽

F. Badran

Keyword(s):

Neural Network ◽

Network Approach ◽

Model Function ◽

Neural Network Approach ◽

Wind Retrieval ◽

Geophysical Model ◽

Geophysical Model Function

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A hybrid analytical-neural network approach to the determination of optimal cutting conditions

Journal of Materials Processing Technology ◽

10.1016/j.jmatprotec.2004.09.019 ◽

2004 ◽

Vol 157-158 ◽

pp. 82-90 ◽

Author(s):

U. Zuperl ◽

F. Cus ◽

B. Mursec ◽

T. Ploj

Keyword(s):

Neural Network ◽

Cutting Conditions ◽

Network Approach ◽

Neural Network Approach

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Neural network approach to the determination of the geophysical model function of the ERS-1 C-band spaceborne radar scatterometer

10.1117/12.271521 ◽

1997 ◽

Author(s):

Sami M. Alhumaidi ◽

W. Linwood Jones

Keyword(s):

Neural Network ◽

Network Approach ◽

Model Function ◽

Neural Network Approach ◽

Geophysical Model ◽

Geophysical Model Function ◽

Spaceborne Radar

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Neural network approach for efficient DOA determination of multiple stochastic EM sources in far-field

2014 International Conference on Numerical Electromagnetic Modeling and Optimization for RF, Microwave, and Terahertz Applications (NEMO) ◽

10.1109/nemo.2014.6995724 ◽

2014 ◽

Author(s):

Zoran Stankovic ◽

Nebojsa Doncov ◽

Bratislav Milovanovic ◽

Johannes Russer ◽

Ivan Milovanovic

Keyword(s):

Neural Network ◽

Far Field ◽

Network Approach ◽

Neural Network Approach ◽

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