Flow Regime Prediction Using Artificial Neural Networks for Air-Water Flow Through 1-5 mm Tubes in Horizontal Plane

被引：0

作者：

Bar, Nirjhar ^{[1
]}

Biswas, Manindra Nath ^{[1
]}

Das, Sudip Kumar ^{[2
]}

机构：

[1] Govt Coll Engn & Leather Technol, Kolkata 700098, India

[2] Univ Calcutta, Dept Chem Engn, Kolkata 700009, India

来源：

INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, VOL 1 | 2015年 / 339卷

关键词：

Flow regime; Multilayer perceptron (MLP); Radial basis function; Support vector machine; Principal component analysis; LIQUID 2-PHASE FLOW; DIAMETER; PATTERNS;

D O I：

10.1007/978-81-322-2250-7_82

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Artificial Neural Network (ANN) based techniques for the classifications of flow regimes in air-water flow through 1-5 mm tubes are presented. 218 data points are based on the experimental investigation in 3 and 4 mm tubes and 2114 data points from various experimental results from the published literature for air-water two-phase flow in small diameter tubes have been used. Five different well known artificial neural network models have been used to predict the flow regime. The ANN model based on Radial Basis Function and Principal Component Analysis gives better predictability over the other networks used.

引用

页码：823 / 830

页数：8

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