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گواهی نمایه سازی مقاله Comparison different neural machine learning models for predicting of nano-size pharmaceuticals

عنوان مقاله: Comparison different neural machine learning models for predicting of nano-size pharmaceuticals
شناسه (COI) مقاله: ICHEC07_476
منتشر شده در هفتمین کنگره ملی مهندسی شیمی در سال ۱۳۹۰
مشخصات نویسندگان مقاله:

j sayyad amin - Chemical Engineering Department, Guilan, Rasht 416353756, Iran
s ashraf - Chemical Engineering Department, Guilan, Rasht 416353756, Iran
m Yousefi - Chemical Engineering Department, Guilan, Rasht 416353756, Iran

خلاصه مقاله:
In this paper, we investigate the applicability of MATLAB to design, train and test an artificial neural network (ANN) to determine the relationships of variables in drug nanoprecipitation using microfluidic reactor. Effective variables on nanoparticle size are computed as ANN inputs and the particle size is considered to be the output. After the training on the input–output process, the AAN predicted values were compared with the other available AAN model which is obtained from INForm software (INForm v3.5, Intelligensys, UK) [1]. Comparing coefficient of determination (R2), regression coefficient (R) values of the MATLAB-ANN model and INForm-ANN model, one can conclude that the first model predicted the particle size with more accuracy than the other

کلمات کلیدی:
Artificial Neural Network, Nanoprecipitation, Microfluidic reactor

صفحه اختصاصی مقاله و دریافت فایل کامل: https://www.civilica.com/Paper-ICHEC07-ICHEC07_476.html