Neural Network Identification of a Circular Hole in the Rectangular Plate

2003 ◽  
pp. 778-783 ◽  
Author(s):  
Grzegorz Piątkowski ◽  
Leonard Ziemiański
Keyword(s):  
Neural Network ◽  
Rectangular Plate ◽  
Circular Hole ◽  
Network Identification

Automated neural network identification of cirques

2021 ◽  
pp. 1-28
Author(s):  
Louis A. Scuderi ◽  
Timothy Nagle-McNaughton
Keyword(s):  
Neural Network ◽  
Network Identification

Sliding Mode Controller with Neural Network Identification

2015 ◽  
Vol 13 (12) ◽  
pp. 3754-3757 ◽  
Author(s):  
Jose Egidio Azzaro ◽  
Ricardo Alfredo Veiga
Keyword(s):  
Neural Network ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Network Identification

A deep residual neural network identification method for uneven dust accumulation on photovoltaic (PV) panels

Energy ◽  
2021 ◽  
pp. 122302
Author(s):  
Siyuan Fan ◽  
Yu Wang ◽  
Shengxian Cao ◽  
Bo Zhao ◽  
Tianyi Sun ◽  
...  
Keyword(s):  
Neural Network ◽  
Identification Method ◽  
Network Identification ◽  
Dust Accumulation

Experimental force reconstruction on plates of arbitrary shape using neural networks

2021 ◽  
Vol 263 (3) ◽  
pp. 3407-3416
Author(s):  
Tyler Dare
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Inverse Problem ◽  
Artificial Neural Network ◽  
Rectangular Plate ◽  
Arbitrary Shape ◽  
Impulsive Force ◽  
Force Reconstruction ◽  
Output Space ◽  
Arbitrary Shapes

Measuring the forces that excite a structure into vibration is an important tool in modeling the system and investigating ways to reduce the vibration. However, determining the forces that have been applied to a vibrating structure can be a challenging inverse problem, even when the structure is instrumented with a large number of sensors. Previously, an artificial neural network was developed to identify the location of an impulsive force on a rectangular plate. In this research, the techniques were extended to plates of arbitrary shape. The principal challenge of arbitrary shapes is that some combinations of network outputs (x- and y-coordinates) are invalid. For example, for a plate with a hole in the middle, the network should not output that the force was applied in the center of the hole. Different methods of accommodating arbitrary shapes were investigated, including output space quantization and selecting the closest valid region.

Analysis of Steel Rectangular Plate with Circular Hole

2021 ◽  
pp. 27-53
Author(s):  
Farzad Hejazi ◽  
Hojjat Mohammadi Esfahani
Keyword(s):  
Rectangular Plate ◽  
Circular Hole

Neural Network Identification of Operating Modes of a Robotic Platform Electric Drive

2019 ◽  
Vol 90 (11) ◽  
pp. 720-724
Author(s):  
D. S. Kurushin ◽  
R. A. Faizrakhmanov ◽  
D. V. Yarullin
Keyword(s):  
Neural Network ◽  
Electric Drive ◽  
Robotic Platform ◽  
Operating Modes ◽  
Network Identification
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