Application of design of experiments and artificial neural network in optimization of ultrasonic energy-assisted transesterification of Sardinella longiceps fish oil to biodiesel
作者： N. Shenbaga Vinayaga Moorthi , P. Arul Franco , K. Ramesh
DOI: 10.1080/02533839.2015.1027740
关键词: Biodiesel production 、 Sardine 、 Transesterification 、 Response surface methodology 、 Biodiesel 、 Pulp and paper industry 、 Methanol 、 Multilayer perceptron 、 Engineering 、 Fish oil 、 Petroleum engineering
摘要: The competent and efficient utilization of feedstocks is highly essential in the transesterification biodiesel from sardine fish oil. identification optimal reaction parameters high importance to maximize yield produced oil at low cost. Application ultrasonic energy-assisted production catalyzed by KOH catalyst has been studied under different conditions. Response surface methodology (RSM) based on central composite rotatable design (CCRD) was employed optimize three important process parameters: methanol/oil molar ratio (X1), concentration (X2), time (X3) for using energy. Artificial neural network (ANN) models with two feed-forward back-propagation architecture, multilayer perceptron networks radial basis function have developed obtain a good correlation between input variables responsible the...
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