Kamairudin, N; Abd Gani, SS; Masoumi, HRF; Basri, M; Hashim, P; Mokhtar, NM; Lane, ME; (2015) Modeling of a natural lipstick formulation using an artificial neural network. RSC Advances , 5 (84) pp. 68632-68638. 10.1039/c5ra12749a.

Preview

Text Lane_Modeling of Natural - lipstick formulation by artificial neural network.pdf Download (595kB) | Preview

Abstract

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%.

Download activity - last month

Export as JSONXMLCSV

Download activity - last 12 months

Export as CSVXMLJSON

Downloads by country - last 12 months

Export as XMLCSVJSON

Archive Staff Only

View Item