Artificial neural networks aid the design of non-carcinogenic azo dyes

1999 ◽  
pp. 503-511
Author(s):  
Les M. Sztandera ◽  
Charles Bock ◽  
Mendel Trachtman ◽  
Janardhan Velga
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Azo Dyes ◽  
Artificial Neural

Semiempirical Quantum Chemical Method and Artificial Neural Networks Applied for λmaxComputation of Some Azo Dyes

2004 ◽  
Vol 44 (6) ◽  
pp. 2047-2050 ◽  
Author(s):  
Guo-Zheng Li ◽  
Jie Yang ◽  
Hai-Feng Song ◽  
Shang-Sheng Yang ◽  
Wen-Cong Lu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Azo Dyes ◽  
Quantum Chemical ◽  
Chemical Method ◽  
Quantum Chemical Method ◽  
Artificial Neural

Nonlinear Modeling for the Degradation of Aqueous Azo Dyes by Combined Advanced Oxidation Processes Using Artificial Neural Networks

2011 ◽  
Vol 6 (1) ◽  
Author(s):  
Masroor Mohajerani ◽  
Mehrab Mehrvar ◽  
Farhad Ein-Mozaffari
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Azo Dyes ◽  
Advanced Oxidation Processes ◽  
Removal Rate ◽  
Advanced Oxidation ◽  
Ultrasonic Power ◽  
Oxidation Processes ◽  
Degradation Rates ◽  
Artificial Neural

One-hidden-layer artificial neural networks (ANNs) using a back-propagation structure have been trained on different sets of experimental data to identify and evaluate the degradation of different azo dyes (Reactive Yellow 84, Reactive Blue 19, Direct Red 23, Direct Red 28, and Acid Blue 193) by photo-Fenton process and combined ozonation and ultrasonolysis processes. Different input variables such as pH, initial concentrations of dyes and ozone, reaction time, ultrasonic power density, and initial concentrations of hydrogen peroxide and ferrous in aqueous solution were employed to model the degradation rates of azo dyes based on the decolorization efficiency and the removal rate using chemical oxygen demand (COD) and total organic carbon (TOC). A new model expression is developed to find the effect of individual parameters and their interactions on the efficiency of organic degradation by advanced oxidation processes.

Determination of S-N curves with the application of artificial neural networks

1999 ◽  
Vol 22 (8) ◽  
pp. 723-728 ◽  
Author(s):  
Artymiak ◽  
Bukowski ◽  
Feliks ◽  
Narberhaus ◽  
Zenner
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Artificial Neural

FUTURE OF ARTIFICIAL NEURAL NETWORKS IN SPACE EXPLORATION AND SPACE ENGINEERING

2018 ◽  
pp. 6-11
Author(s):  
Kobiljon Kh. Zoidov ◽  
◽  
Svetlana V. Ponomareva ◽  
Daniel I. Serebryansky ◽  
◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Space Exploration ◽  
Artificial Neural

Bankruptcy Prediction Models: A Bet on Artificial Neural Networks

2012 ◽  
Vol 3 (2) ◽  
pp. 48-50
Author(s):  
Ana Isabel Velasco Fernández ◽  
◽  
Ricardo José Rejas Muslera ◽  
Juan Padilla Fernández-Vega ◽  
María Isabel Cepeda González
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Prediction Models ◽  
Bankruptcy Prediction ◽  
Artificial Neural
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