Prediction of functional properties of nano TiO2 coated cotton composites by artificial neural network

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24210%2F21%3A00008876" target="_blank" >RIV/46747885:24210/21:00008876 - isvavai.cz</a>

Alternative codes found

RIV/46747885:24620/21:00008876

Result on the web

<a href="https://www.nature.com/articles/s41598-021-91733-y" target="_blank" >https://www.nature.com/articles/s41598-021-91733-y</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41598-021-91733-y" target="_blank" >10.1038/s41598-021-91733-y</a>

Result language

angličtina

Original language name

Prediction of functional properties of nano TiO2 coated cotton composites by artificial neural network

Original language description

This paper represents the efficiency of machine learning tool, i.e., artificial neural network (ANN), for the prediction of functional properties of nano titanium dioxide coated cotton composites. A comparative analysis was performed between the predicted results of ANN, multiple linear regression (MLR) and experimental results. ANN was applied to map out the complex input-output conditions to predict the optimal results. A backpropagation ANN model called a multilayer perceptron (MLP), trained with Bayesian regularization were used in this study. The amount of chemicals and reaction time were selected as input variables and the amount of titanium dioxide coated on cotton, self-cleaning efficiency, antimicrobial efficiency and ultraviolet protection factor were analysed as output results. The accuracy of the proposed algorithm was evaluated and compared with MLR results. The obtained results reveal that MLP provides efficient results that are statistically significant in the prediction of functional properties (p95%) indicates that there is a strong correlation between the measured and predicted functional properties with a trivial mean absolute error and root mean square errors values. MLP model is suitable for the functional properties and can be used for the investigation of other properties of nano coated fabrics.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10700 - Other natural sciences

Project

<a href="/en/project/EF16_025%2F0007293" target="_blank" >EF16_025/0007293: Modular platform for autonomous chassis of specialized electric vehicles for freight and equipment transportation</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Scientific Reports

ISSN

2045-2322

e-ISSN

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Volume of the periodical

11

Issue of the periodical within the volume

1

Country of publishing house

DE - GERMANY

Number of pages

11

Pages from-to

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UT code for WoS article

000663784500005

EID of the result in the Scopus database

2-s2.0-85109314725