A Prediction System of Economic Parameters in the Textile Industry Using Artificial Neural Networks

2016 ◽  
Author(s):  
Guest Editor Jianping Du
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Textile Industry ◽  
Prediction System ◽  
Economic Parameters ◽  
Artificial Neural

scholarly journals APPLICATION OF BACKPROPAGATION NEURAL NETWORKS IN PREDICTING RAINFALL DATA IN AMBON CITY

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Yopi Andry Lesnussa ◽  
C. G. Mustamu ◽  
F. Kondo Lembang ◽  
M. W. Talakua
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Human Life ◽  
Prediction System ◽  
Air Velocity ◽  
Rainfall Prediction ◽  
Accuracy Level ◽  
Backpropagation Method ◽  
Iteration Number ◽  
Artificial Neural

The Artificial Neural Networks is a process of information system on certain traits which as representatives of the human neural networks. The Artificial Neural Networks can be applied in every area of human life, one of them is environment especially about prediction of climate or weather. In this research, the artificial neural network is used to predict the rainfall with Backpropagation method and using MATLAB software. The other meteorology parameters used to predict the rainfall are air temperature, air velocity and air pressure. The result showed less accuracy level is 80% by using alpha 0,7, iteration number (epoch) 10000 and MSE value = 0,0218. Therefore, the result of rainfall prediction system is accurate.

scholarly journals Employment of advanced oxidation processes in the degradation of a textile dye mixture: evaluation of reaction parameters, kinetic study, toxicity and modeling by artificial neural networks

2021 ◽  
Vol 25 ◽  
pp. e12
Author(s):  
Marcos André Soares de Oliveira ◽  
Naiana Santos da Cruz Santana Neves ◽  
Rayany Magali da Rocha Santana ◽  
Alex Leandro Andrade de Lucena ◽  
Léa Elias Mendes Carneiro Zaidan ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Water Resources ◽  
Organic Contaminants ◽  
Textile Industry ◽  
Advanced Oxidation Processes ◽  
Advanced Oxidation ◽  
Textile Dye ◽  
Oxidation Processes ◽  
Artificial Neural

Organic contaminants in industrial effluents threaten the quality of water resources, especially due to their resistance to natural degradation. The textile industry gain relevance, considering that it generates large volumes. This work aimed to evaluate the efficiency of different advanced oxidation processes (AOP) for the degradation of the mixture textile dyes in solution. After optimization of the main parameters involved in the applied processes and systems, the AOP with greater efficiency in the degradation of the compounds was the photo-Fenton/UV-C (92%) after 360 min of treatment. The experimental data showed a better fit to the Chan and Chu kinetic model and trough an evaluation using artificial neural networks it was possible to predict the maximum degradation achievable by the dye mixture. The toxicity assays, using multiple species of seeds indicated a treated solution with no toxic effects and that the applied methodology can be used without affecting the water resources.

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