预测井眼稳定性的力学化学耦合方法

在井眼力学稳定性评价的基础上，将硬脆性页岩水化后岩石强度等参数的变化规律用于页岩水化前后坍塌压力变化的对比分析，结果表明，地层坍塌压力当量密度随页岩水化程度的增加逐渐升高。给出了预测井眼稳定性的力学化学耦合方法，并将该方法应用于现场生产中，取得了较好的预测效果     

A comparison of backpropagation and general regression neural networks in quantative trace metal analysis using anodic stripping voltammetry and cybernetic instrumentation

A comparison is made between backpropagation and general regression neural networks for the prediction of parts per billion lead concentration when used to process data obtained from digested curry powder by the electrochemical analysis method of differential pulse, anodic stripping at a thin film mercury electrode (TFME). Two data sets are used, one requiring the net to classify an unknown analytical data vector into one of a number of previously learnt concentrations, and one requiring the net to predict the probable concentration of an unknown sample by interpolation of the already learnt concentrations. For both of these data sets the general regression neural network is shown to train faster and to provide results superior to those obtained by backpropagation.     

f—x域内提高地震资料的信噪比

在 f-x 域,地震记录可以表示成有限个调频调幅正弦波的叠合,叠合的结果是一个连续且光滑的函数。我们可以用一个简单的 n 次多项式去逼近这个函数。本文提出了一种在 f-x 域用最小平方拟合原理消除随机噪声的新方法,并证明了在噪声为自噪以及空间采样足够密的条件下,拟合结果与噪声无关,即 f-x 域最小平方拟合处理可以有效地消除记录上的随机白噪,而对有效信号的破坏甚微。由于理论上允许振幅值及同相轴形态在空间上发生变化,因而该方法不具有混波作用,是高分辨率处理的理想工具。     

钢铁企业价格预测决策模型体系研究

通过对钢铁企业现行价格管理体系的分析 ,建立了钢铁企业价格预测决策模型体系。充分利用大量的定性、定量信息 ,并把趋势预测和因果预测技术相结合 ,采用组合预测模型对价格进行预测 ,最后对预测出来的多方案进行模糊综合评价 ,给出推荐方案顺序。实际应用表明 ,模型体系是有效的。     

局部剩余偏移与常速叠前偏移成像

如果需要将一个特定局部时空域中的地震反射波归位到它们的实际位置,则我们不必在整个时空域而只需在这个局部时空域对其进行偏移,同样能达到波场归位的目的。其差別仅是采用的速度不同而已.这样能大大地减小偏移的作用区域。采用这种局部偏移的方法进行常速叠前偏移结果的剩余速度偏移,可以完全消除叠前偏移剖面上由于速度变化引起的倾斜反射界面的错断现象。这样在进行叠前偏移时可采用较少的速度个数,减少叠前偏移的计算量。采用该方法作剩余速度偏移可以减少波场成像时的计算量,从而使得常速叠前偏移成为一种处理效果好、处理效率高的实用处理技术。     

Melt index prediction by weighted least squares support vector machines

Melt index is considered an important quality variable determining product specifications. Reliable prediction of melt index (MI) is crucial in quality control of practical propylene polymerization processes. In this paper a least squares support vector machines (LS‐SVM) soft‐sensor model of propylene polymerization process is developed to infer the MI of polypropylene from other process variables. Considering the use of a SSE cost function without regularization might lead to less robust estimates; the weighted least squares support vector machines (weighted LS‐SVM) approach of propylene polymerization process is further proposed to obtain a robust estimation of melt index. The performance of standard SVM model is taken as a basis of comparison. A detailed comparison research among the standard SVM, LS‐SVM, and weighted LS‐SVM models is carried out. The research results confirm the effectiveness of the presented methods. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 285–289, 2006     

Analysis of supersaturation and nucleation in a moving solution droplet with flowing supercritical carbon dioxide

A supercritical antisolvent (SAS) process is employed for production of solid nanoparticles from atomized droplets of dilute solution in a flowing supercritical carbon dioxide (SC CO₂) stream by attaining extremely high, very rapid, and uniform supersaturation. This is facilitated by a two‐way mass transfer of CO₂ and solvent, to and from the droplet respectively, rendering rapid reduction in equilibrium solubility of the solid solute in the ternary solution. The present work analyses the degree of supersaturation and nucleation kinetics in a single droplet of cholesterol solution in acetone during its flight in a flowing SC CO₂ stream. Both temperature and composition are assumed to be uniform within the droplet, and their variations with time are calculated by balancing the heat and mass transfer fluxes to and from the droplet. The equilibrium solubility of cholesterol with CO₂ dissolution has been predicted as being directly proportional to the Partial Molar Volume Fraction (PMVF) of acetone in the binary (CO₂–acetone) system. The degree of supersaturation has been simulated up to the time required to attain almost zero cholesterol solubility in the droplet for evaluating the rate of nucleation and the size of the stable critical nuclei formed. The effects of process parameters have been analysed in the pressure range of 7.1–35.0 MPa, temperature range of 313–333 K, SC CO₂ flow rate of 0.1136–1.136 mol s^?1, the ratio of the volumetric flow rates of CO₂‐to‐solution in the range of 100–1000, and the initial mole fraction of cholesterol in acetone solution in the range of 0.0025–0.010. The results confirm an extremely high and rapid increase in degree of supersaturation, very high nucleation rates and stable critical nucleus diameter of the order of a nanometre. Copyright © 2005 Society of Chemical Industry     

On the relationships among latent variables and residuals in PLS path modeling: The formative-reflective scheme

A new approach for the estimation and the validation of a structural equation model with a formative-reflective scheme is presented. The basis of the paper is a proposal for overcoming a potential deficiency of PLS path modeling. In the PLS approach the reflective scheme assumed for the endogenous latent variables (LVs) is inverted; moreover, the model errors are not explicitly taken into account for the estimation of the endogenous LVs. The proposed approach utilizes all the relevant information in the formative manifest variables (MVs) providing solutions which respect the causal structure of the model. The estimation procedure is based on the optimization of the redundancy criterion. The new approach, entitled redundancy analysis approach to path modeling (RA-PM) is compared with both traditional PLS Path Modeling and LISREL methodology, on the basis of real and simulated data.     

打括隧道监控量测结果的一元非线性回归分析

针对黄织铁路工程打括隧道923延米V级围岩土质地段,根据施工中的地质动态对打括隧道初期支护中监控量测结果进行一元非性线回归分析,以制定科学施工方案和确定合理支护参数,保证工程质量和作业的安全性。     

SECANT-FUZZY LINEAR REGRESSION METHOD FOR HARMONIC COMPONENTS ESTIMATION IN A POWER SYSTEM

In order to avoid unnecessary damage of electrical equipments and installations,high quality power should be delivered to the end user and strict control on frequency should be made, Therefore, it is important to estimate the power system's harmonic components with higher accuracy. This paper presents a new approach for estimating harmonic component in a power system using secant - fuzzy linear regression method. In this approach the non - sinusoidal voltage or current waveform is written as I linear function. The coefficient of this function is assumed to be fuzzy number with a membership function that has center and spread value. The time dependent quantity is written as Taylor series with two different time dependent quantities. The objective is to use the sample obtained from the transmission line to find the power system harmonic components and frequencies. We used an experimental voltage signal from a sub power station as a numerical test.