Determination of optical properties of Al80Mn20 quasi-crystalline alloy using neural networks

2006 ◽  
Vol 777 (1-3) ◽  
pp. 45-51 ◽  
Author(s):  
Ch. Bourouis ◽  
A. Meddour ◽  
A.K. Moussaoui
Keyword(s):  
Neural Networks ◽  
Optical Properties ◽  
Crystalline Alloy

Operational Determination of the Activated Sludge Process Using Neural Networks

1992 ◽  
Vol 26 (9-11) ◽  
pp. 2461-2464 ◽  
Author(s):  
R. D. Tyagi ◽  
Y. G. Du
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Steady State ◽  
Activated Sludge ◽  
Feedforward Neural Network ◽  
Training Data ◽  
Activated Sludge Process

A steady-statemathematical model of an activated sludgeprocess with a secondary settler was developed. With a limited number of training data samples obtained from the simulation at steady state, a feedforward neural network was established which exhibits an excellent capability for the operational prediction and determination.

scholarly journals Determination of the geophysical model function of the ERS-1 scatterometer by the use of neural networks

1998 ◽  
Vol 103 (C6) ◽  
pp. 12853-12868 ◽  
Author(s):  
Carlos Mejia ◽  
Sylvie Thiria ◽  
Ngan Tran ◽  
Michel Crépon ◽  
Fouad Badran
Keyword(s):  
Neural Networks ◽  
Model Function ◽  
Geophysical Model ◽  
Geophysical Model Function

scholarly journals Optical Characterization of Ultra-Thin Films of Azo-Dye-Doped Polymers Using Ellipsometry and Surface Plasmon Resonance Spectroscopy

Photonics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 41
Author(s):  
Najat Andam ◽  
Siham Refki ◽  
Hidekazu Ishitobi ◽  
Yasushi Inouye ◽  
Zouheir Sekkat
Keyword(s):  
Refractive Index ◽  
Optical Properties ◽  
Surface Plasmon Resonance ◽  
Surface Plasmon ◽  
Spectroscopic Ellipsometry ◽  
Plasmon Resonance ◽  
Complex Refractive Index ◽  
Resonance Spectroscopy ◽  
Doped Polymers

The determination of optical constants (i.e., real and imaginary parts of the complex refractive index (nc) and thickness (d)) of ultrathin films is often required in photonics. It may be done by using, for example, surface plasmon resonance (SPR) spectroscopy combined with either profilometry or atomic force microscopy (AFM). SPR yields the optical thickness (i.e., the product of nc and d) of the film, while profilometry and AFM yield its thickness, thereby allowing for the separate determination of nc and d. In this paper, we use SPR and profilometry to determine the complex refractive index of very thin (i.e., 58 nm) films of dye-doped polymers at different dye/polymer concentrations (a feature which constitutes the originality of this work), and we compare the SPR results with those obtained by using spectroscopic ellipsometry measurements performed on the same samples. To determine the optical properties of our film samples by ellipsometry, we used, for the theoretical fits to experimental data, Bruggeman’s effective medium model for the dye/polymer, assumed as a composite material, and the Lorentz model for dye absorption. We found an excellent agreement between the results obtained by SPR and ellipsometry, confirming that SPR is appropriate for measuring the optical properties of very thin coatings at a single light frequency, given that it is simpler in operation and data analysis than spectroscopic ellipsometry.

Determination of application volume for coffee plantations using artificial neural networks and remote sensing

2021 ◽  
Vol 184 ◽  
pp. 106096
Author(s):  
Mailson Freire de Oliveira ◽  
Adão Felipe dos Santos ◽  
Elizabeth Haruna Kazama ◽  
Glauco de Souza Rolim ◽  
Rouverson Pereira da Silva
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Coffee Plantations ◽  
Artificial Neural ◽  
Application Volume
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