Transparent predictive modelling of the twin screw granulation process using a compensated interval type-2 fuzzy system.
Transparent predictive modelling of the twin screw granulation process using a compensated interval type-2 fuzzy system.
复制标题
使用补偿区间 2 型模糊系统对双螺杆造粒过程进行透明预测建模。
DOI：
10.1016/j.ejpb.2017.12.015
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
AlAlaween WH
中科院分区：
文献类型：
--
作者：
AlAlaween WH
在这项研究中，提出了一个新的系统建模框架，该框架使用机器学习来描述造粒过程。首先，建立了区间2型模糊模型，以预测制药行业双螺杆造粒（TSG）生产的颗粒的性能。其次，在框架中集成高斯混合模型（GMM），以表征模糊模型产生的误差残差。这样做是为了通过考虑不确定性和/或任何其他未建模的行为（随机或其他）来改进模型。所有提出的建模算法都通过一系列实验室规模的实验进行了验证。TSG产生的颗粒大小被成功预测，其中大多数预测在95%的置信区间内拟合。
In this research, a new systematic modelling framework which uses machine learning for describing the granulation process is presented. First, an interval type-2 fuzzy model is elicited in order to predict the properties of the granules produced by twin screw granulation (TSG) in the pharmaceutical industry. Second, a Gaussian mixture model (GMM) is integrated in the framework in order to characterize the error residuals emanating from the fuzzy model. This is done to refine the model by taking into account uncertainties and/or any other unmodelled behaviour, stochastic or otherwise. All proposed modelling algorithms were validated via a series of Laboratory-scale experiments. The size of the granules produced by TSG was successfully predicted, where most of the predictions fit within a 95% confidence interval.