Title :
A Novel Neuro-Fuzzy Model for Supercritical Fluid Extraction
Author :
Yang, Simon X. ; Zeng, Jin ; Guo, Chen ; Sun, Fuchun
Abstract :
Supercritical fluid extraction is an environmental friendly separation technique in food and chemical industry that exploits the solvent properties of fluid near the critical point. Modeling of the solubility of biomaterials is an essential issue in supercritical fluid extraction. In this paper, a novel neuro-fuzzy model is developed to model the relationship between pressure and yield of biomaterial. The results using the proposed neuro-fuzzy model are generally better than those using the conventional model by Peng-Robinson equation of state. The effectiveness of the proposed approaches was demonstrated by simulation and comparison studies
Keywords :
chemical industry; food manufacturing; fuzzy neural nets; production engineering computing; separation; biomaterials; chemical industry; environmental friendly separation technique; food industry; neuro-fuzzy model; supercritical fluid extraction; Artificial neural networks; Chemical industry; Data mining; Equations; Fuzzy neural networks; Fuzzy sets; Multi-layer neural network; Neural networks; Solids; Temperature;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614971
