Comparison of response surface methodology (RSM) and artificial neural networks (ANN) towards efficient extraction of artemisinin from Artemisia annua

Industrial Crops and Products

Volumn 58, Issue , 2014, Pages 15-24

  Pilkington, Josh L ^a   Preston, Chris ^b   Gomes, Rachel L ^a  

^a UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^b Bio Project Consulting Ltd   (United Kingdom)

Author keywords

Artemisia annua; Artemisinin; Artificial neural network; Extraction; Malaria; Response surface methodology

Indexed keywords

COMMERCE; ETHERS; NEURAL NETWORKS; OPTIMIZATION; RECOVERY; SECONDARY RECOVERY; SURFACE PROPERTIES;

ABSOLUTE AVERAGE DEVIATION; ARTEMISIA ANNUA; ARTEMISININ; ARTIFICIAL NEURAL NETWORK MODELS; CENTRAL COMPOSITE DESIGNS; COEFFICIENT OF DETERMINATION; MALARIA; RESPONSE SURFACE METHODOLOGY;

EXTRACTION;

ARTIFICIAL NEURAL NETWORK; DRUG; ETHER; HERB; MALARIA; MARKET SYSTEM; NUMERICAL MODEL; SOLUBILIZATION; SOLVENT;

EID: 84899682955     PISSN: 09266690     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.indcrop.2014.03.016     Document Type: Article

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