Modeling of a natural lipstick formulation using an artificial neural network
RSC Advances, ISSN: 2046-2069, Vol: 5, Issue: 84, Page: 68632-68638
2015
- 6Citations
- 29Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
An artificial neural network (ANN) was applied in conjunction with experimental data from a mixture of experimental designs to predict the melting point of a lipstick formulation. The experimental data were utilized for training and testing the suggested model. By using the ANN performance results, the optimum parameters were found to be pitaya seed oil 25% w/w, virgin coconut oil 37% w/w, beeswax 17% w/w, candelilla wax 2% w/w, and carnauba wax 2% w/w. The relative standard error under these parameters was only 0.8772%. It was found that batch back-propagation (BBP) gave the optimal algorithm and topology with a configuration of five inputs, two hidden nodes and one output node; the most important parameter was the carnauba wax content with a relative importance of 24.5%.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84939518855&origin=inward; http://dx.doi.org/10.1039/c5ra12749a; http://xlink.rsc.org/?DOI=C5RA12749A; http://pubs.rsc.org/en/content/articlepdf/2015/RA/C5RA12749A; https://xlink.rsc.org/?DOI=C5RA12749A; https://dx.doi.org/10.1039/c5ra12749a; https://pubs.rsc.org/en/content/articlelanding/2015/ra/c5ra12749a
Royal Society of Chemistry (RSC)
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