首页> 外文会议>International Conference on Machine Learning and Cybernetics >LSSVM model of oil holdup of oil-water two phase flow using thermal method based on HHT
【24h】

LSSVM model of oil holdup of oil-water two phase flow using thermal method based on HHT

机译:基于HHT的热法,LSSVM油水储油两相流型型号

获取原文

摘要

A new model based on least square support vector machines (LSSVM) and Hilbert-Huang transform (HHT) has been proposed for the first time, which is capable of forecasting oil holdup of oil-water two phase flow. Owing to the temperature signal of oil-water two phase flow is greatly disturbed by noises, which results in a limited measurement range of oil holdup. In order to solve the problem, a new signal processing method based on the improved HHT is used. With its ideal performance on local adaptability and time-frequency analysis, noises are removed. Experimental studies were carried out to compare the HHT with the wavelet transform. The instantaneous fluctuated amplitude and the standard deviation are obtained form the last residue component of HHT, together with total flux were employed as inputs of LSSVM model. In order to improve the predictive accuracy of the LSSVM model, a Genetic Arithmetic (GA) has been adopted to determine the optimal parameters of LSSVM automatically. The experiment results show that the average measurement error of LSSVM model was 0.542% in the range of 8% to 90% oil holdup.
机译:首次提出了一种基于最小二乘支持向量机(LSSVM)和HILBERT-HUANG变换(HHT)的新模型,其能够预测油水两相流量的储存。由于油水的温度信号,两个相流受到噪声的极大地受到干扰,这导致有限的储油量程范围。为了解决问题,使用了一种基于改进HHT的新信号处理方法。凭借其局部适应性和时频分析的理想性能,噪音被拆除。进行实验研究以将HHT与小波变换进行比较。将瞬时波动幅度和标准偏差形成为HHT的最后残基组分,将总通量一起用作LSSVM模型的输入。为了提高LSSVM模型的预测准确性,已经采用了遗传算术(GA)来自动确定LSSVM的最佳参数。实验结果表明,LSSVM型号的平均测量误差为0.542%,范围为8%至90%的储油。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号