Flow injection analysis of fluoride: optimization of experimental conditions and non-linear calibration using artificial neural networks

The Analyst ◽  
2000 ◽  
Vol 125 (12) ◽  
pp. 2376-2380 ◽  
Author(s):  
Yongyao Zhou ◽  
Aixia Yan ◽  
Hongping Xu ◽  
Ketai Wang ◽  
Xingguo Chen ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Flow Injection ◽  
Flow Injection Analysis ◽  
Linear Calibration ◽  
Experimental Conditions ◽  
Non Linear ◽  
Artificial Neural ◽  
Optimization Of Experimental Conditions

Artificial Neural Networks in Multivariate Calibration

1993 ◽  
Vol 1 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Tormod Næs ◽  
Knut Kvaal ◽  
Tomas Isaksson ◽  
Charles Miller
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Network Architecture ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Calibration Method ◽  
Linear Calibration ◽  
Feed Forward Network ◽  
Non Linear ◽  
Artificial Neural

This paper is about the use of artificial neural networks for multivariate calibration. We discuss network architecture and estimation as well as the relationship between neural networks and related linear and non-linear techniques. A feed-forward network is tested on two applications of near infrared spectroscopy, both of which have been treated previously and which have indicated non-linear features. In both cases, the network gives more precise prediction results than the linear calibration method of PCR.

scholarly journals Analysis of Cantilever Beam Deflection under Uniformly Distributed Load using Artificial Neural Networks

2019 ◽  
Vol 255 ◽  
pp. 06004
Author(s):  
T.M.Y.S Tuan Ya ◽  
Reza Alebrahim ◽  
Nadziim Fitri ◽  
Mahdi Alebrahim
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Cantilever Beam ◽  
Training Data ◽  
Beam Deflection ◽  
Problem Solver ◽  
Distributed Load ◽  
Uniformly Distributed Load ◽  
Non Linear ◽  
Artificial Neural

In this study the deflection of a cantilever beam was simulated under the action of uniformly distributed load. The large deflection of the cantilever beam causes the non-linear behavior of beam. The prupose of this study is to predict the deflection of a cantilever beam using Artificial Neural Networks (ANN). The simulation of the deflection was carried out in MATLAB by using 2-D Finite Element Method (FEM) to collect the training data for the ANN. The predicted data was then verified again through a non linear 2-D geometry problem solver, FEM. Loads in different magnitudes were applied and the non-linear behaviour of the beam was then recorded. It was observed that, there is a close agreement between the predicted data from ANN and the results simulated in the FEM.

scholarly journals Hybrid Spectral Unmixing: Using Artificial Neural Networks for Linear/Non-Linear Switching

2017 ◽  
Vol 9 (8) ◽  
pp. 775 ◽  
Author(s):  
Asmau Ahmed ◽  
Olga Duran ◽  
Yahya Zweiri ◽  
Mike Smith
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Spectral Unmixing ◽  
Non Linear ◽  
Artificial Neural
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