Advantages of neurofuzzy logic against conventional experimental design and statistical analysis in studying and developing direct compression formulations
被引:45
作者:
论文数: 引用数:
h-index:
机构:
Landin, Mariana
[1
]
Rowe, R. C.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Bradford, Inst Pharmaceut Innovat, Bradford BD7 1DP, W Yorkshire, EnglandUniv Santiago de Compostela, Fac Farm, Dept Farm & Tecnol Farmaceut, Santiago De Compostela 15782, Spain
Rowe, R. C.
[2
]
York, P.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Bradford, Inst Pharmaceut Innovat, Bradford BD7 1DP, W Yorkshire, EnglandUniv Santiago de Compostela, Fac Farm, Dept Farm & Tecnol Farmaceut, Santiago De Compostela 15782, Spain
York, P.
[2
]
机构:
[1] Univ Santiago de Compostela, Fac Farm, Dept Farm & Tecnol Farmaceut, Santiago De Compostela 15782, Spain
[2] Univ Bradford, Inst Pharmaceut Innovat, Bradford BD7 1DP, W Yorkshire, England
Neurofuzzy logic;
Data mining;
Direct compression tablets;
Design of experiments;
Response surface methodology;
ARTIFICIAL NEURAL-NETWORK;
OPTIMIZATION;
D O I:
10.1016/j.ejps.2009.08.004
中图分类号:
R9 [药学];
学科分类号:
1007 ;
摘要:
This study has investigated the utility and potential advantages of an artificial intelligence technology neurofuzzy logic - as a modeling tool to study direct compression formulations. The modeling performance was compare with traditional statistical analysis. From results it can be stated that the normalized error obtained from neurofuzzy logic was lower. Compared to the multiple regression analysis neurofuzzy logic showed higher accuracy in prediction for the five Outputs studied. Rule sets generated by neurofuzzy logic are completely in agreement with the findings based on statistical analysis and advantageously generate understandable and reusable knowledge. Neurofuzzy logic is easy and rapid to apply and outcomes provided knowledge not revealed via statistical analysis. (C) 2009 Elsevier B.V. All rights reserved.