期刊
COMPUTATIONAL & APPLIED MATHEMATICS
卷 37, 期 4, 页码 4321-4341出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s40314-018-0578-6
关键词
Annular; Adaptive neuro-fuzzy inference system; Three-phase
The use of adaptive neuro-fuzzy inference system (ANFIS) has been reported for predicting the volume fractions in a gas-oil-water multiphase system. In fact, the volume fractions in the annular three-phase flow are measured based on a dual energy metering system consisting of and and one NaI detector using ANFIS. Since the summation of volume fractions is constant, therefore ANFIS must predict only two volume fractions. In this study, three ANFIS networks are applied. The first is utilized to predict the gas and water volume fractions. The next one is applied to predict the gas and oil, and the last one is used to predict the water and oil volume fractions. In the next step, ANFIS networks must be trained based on numerically obtained data from MCNP-X code. Then, the average testing errors of these three networks are computed and compared. The network with the least error has been selected as the best predictor model.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据