Application of artificial neural network in predicting the extraction yield of essential oils of Diplotaenia cachrydifolia by supercritical fluid extraction

By M. Khajeh, Mansour Ghaffari Moghaddam, M. Shakeri. 2012

103 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Biomedical Engineering, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/f37f9ee48790a3028c018f6595ecb162d67ebefc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Himan Nourbakhsh
2. Mahmoud Omid
3. H. Mirsaeedghazi
4. C. Preston
5. Rachel L. Gomes
6. J. Pilkington
7. Z. Emam-djomeh
8. S. Moini

Citations in the corpus

• Prediction of red plum juice permeate flux during membrane processing with ANN optimized using RSM (2014, methodology): “The testing data was used to assess the predictive ability of the generated model (Khajeh et al., 2012).”
• Comparison of response surface methodology (RSM) and artificial neural networks (ANN) towards efficient extraction of artemisinin from Artemisia annua (2014, background): “, 2012), essential ils from Diplotaenia cachrydifolia (Khajeh et al., 2012), coumarin rom Cuscuta reflexa (Mitra et al.”