Artificial neural network modeling of plastic viscosity, yiled point and apparent viscosity for wheat starch solutions

Publish Year: 1390
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:

IPEC03_028

تاریخ نمایه سازی: 7 تیر 1393

Abstract:

Wheat starch is a carbohydrate polymer which is widely used in drilling muds in order to increase viscosity and decrease fluid loss. Rheological properties ofdrilling muds such as plastic viscosity, yield point and apparent viscosity play an essential role in selecting the most optimum composition of drilling mud underdiverse conditions. In this study, an artificial neural network system was used to predict plastic viscosity (PV), yield point (YP) and apparent viscosity (AV) ofwheat starch solutions. Multi-layer feed forward method was applied in the architecture of the artificial neural network due to its high accuracy. To predict plastic viscosity and yield point, the structure of feed-forward neural network wasdefinite 2:2:1 which refers to input layer, hidden layer and output layer. Thecoefficient of determination (R2) values obtained for training and validation data revealed how this approach is effective in estimating the output layer. The best structure of artificial neural network architecture obtained 3:3:1 for predicting apparent viscosity. R2 value (R2=0.994) of testing data obtained by artificial neural network system revealed the high accuracy of this approach in estimating apparent viscosity.

Authors

Meisam Mirarab Razi

Iran University of Science and Technology, Department of Chemical Engineering, Tehran, Iran

Mohammad Mazidi

Iran University of Science and Technology, Department of Chemical Engineering, Tehran, Iran

Fatemeh Mirarab Razi

Mathematics and Computer Science Department, Amirkabir University of Technology, Tehran, Iran

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