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Diagnostic Analyses of the Modified Convective Vorticity Vector in Non-uniformly Saturated Moist Flow 被引量:5
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作者 YANG Shuai WANG Dong-Hai 《Atmospheric and Oceanic Science Letters》 2009年第3期142-147,共6页
Because the real atmosphere is non-uniformly saturated, the generalized potential temperature is introduced. The convective vorticity vector, which can depict the occurrence and development of mesoscale deep convectiv... Because the real atmosphere is non-uniformly saturated, the generalized potential temperature is introduced. The convective vorticity vector, which can depict the occurrence and development of mesoscale deep convective systems, is modified and re-derived in a nonuniformly saturated moist atmosphere (C*). Then, a case study is performed for a frontal rainfall event which occurred near the middle and lower reaches of the Yangtze River in China. The diagnostic results of C* show that, in the lower troposphere, the vertical component of C* (Cz*) can diagnose developments and movements of precipitation and convection better than those of Cm (Cmz, in saturated moist flow) and C (Cz, in dry flow). Cz* is a good predictor for precipitation analyses as well. 展开更多
关键词 non-uniform saturation generalized potentialtemperature MODIFIED convective vorticity vector
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基于非均匀矢量量化的孤立数字语音识别
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作者 陈在 《重庆邮电学院学报(自然科学版)》 1992年第1期40-47,共8页
本文讨论了基于非均匀矢量量化、隐马尔可夫模型(HMM)的孤立数字语音识别系统。在现有的连续密度隐马尔可夫模型多说话人孤立数字识别系统中,通常采用 LBG 算法建立矢量码本,并采用全搜索识别算法,这样的结果限制了识别精度和识别速度... 本文讨论了基于非均匀矢量量化、隐马尔可夫模型(HMM)的孤立数字语音识别系统。在现有的连续密度隐马尔可夫模型多说话人孤立数字识别系统中,通常采用 LBG 算法建立矢量码本,并采用全搜索识别算法,这样的结果限制了识别精度和识别速度。本文提出了一种新的系统算法,即用非均匀矢量量化(Non-Uniform Vector Quantization——NUVQ)取代原矢量量化部份,实验结果证明,本系统在识别速度和识别精度上都有了较大的改善。 展开更多
关键词 语音识别 非均匀 矢量量化
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Artificial intelligence method for predicting the maximum stress of an off-center casing under non-uniform ground stress with support vector machine 被引量:2
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作者 DI QinFeng WU ZhiHao +4 位作者 CHEN Tao CHEN Feng WANG WenChang QIN GuangXu CHEN Wei 《Science China(Technological Sciences)》 SCIE EI CAS CSCD 2020年第12期2553-2561,共9页
The situation of an off-center casing under non-uniform ground stress can occur in the process of drilling a salt-gypsum formation,and the related casing stress calculation has not yet been solved analytically. In add... The situation of an off-center casing under non-uniform ground stress can occur in the process of drilling a salt-gypsum formation,and the related casing stress calculation has not yet been solved analytically. In addition,the experimental equipment in many cases cannot meet the actual conditions and the experimental cost is very high. These comprehensive factors cause the existing casing design to not meet the actual conditions and cause casing deformation,affecting the drilling operation in Tarim oil field. The finite element method is the only effective method to solve this problem at present,but the re-modelling process is time-consuming because of the changes in the parameters,such as the cement properties,casing centrality,and the casing size. In this article,an artificial intelligence method based on support vector machine(SVM) to predict the maximum stress of an offcenter casing under non-uniform ground stress has been proposed. After a program based on a radial basis function(RBF)-support vector regression(SVR)(ε-SVR) model was established and validated,we constructed a data sample with a capacity of 120 by using the finite element method,which could meet the demand of the nine-factor ε-SVR model to predict the maximum stress of the casing. The results showed that the artificial intelligence prediction method proposed in this manuscript had satisfactory prediction accuracy and could be effectively used to predict the maximum stress of an off-center casing under complex downhole conditions. 展开更多
关键词 support vector machine maximum stress off-center casing non-uniform ground stress oil and gas wells
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