液、塑限联合试验成果的数值分析方法

确定土的液限和塑限是土工试验的重要内容。根据液、塑限参数的相关性,采用最小二乘数法、解析法、逐次分半算法等数值计算方法可确定出液、塑限值,同时相关计算结果的置信度、精度分析比较表明,逐次分半算法和解析法精度较高,是工程应用中液塑限成果的方便、快捷、准确的计算方法。

Geophysical data sparse reconstruction based on L0-norm minimization

Missing data are a problem in geophysical surveys, and interpolation and reconstruction of missing data is part of the data processing and interpretation. Based on the sparseness of the geophysical data or the transform domain, we can improve the accuracy and stability of the reconstruction by transforming it to a sparse optimization problem. In this paper, we propose a mathematical model for the sparse reconstruction of data based on the LO-norm minimization. Furthermore, we discuss two types of the approximation algorithm for the LO- norm minimization according to the size and characteristics of the geophysical data： namely, the iteratively reweighted least-squares algorithm and the fast iterative hard thresholding algorithm. Theoretical and numerical analysis showed that applying the iteratively reweighted least-squares algorithm to the reconstruction of potential field data exploits its fast convergence rate, short calculation time, and high precision, whereas the fast iterative hard thresholding algorithm is more suitable for processing seismic data, moreover, its computational efficiency is better than that of the traditional iterative hard thresholding algorithm.

Approach to estimation of vehicle-road longitudinal friction coefficient

According to the road adaptive requirements for the vehicle longitudinal safety assistant system an estimation method of the road longitudinal friction coefficient is proposed.The method can simultaneously be applied to both the high and the low slip ratio conditions. Based on the simplified magic formula tire model the road longitudinal friction coefficient is preliminarily estimated by the recursive least squares method.The estimated friction coefficient and the tires model parameters are considered as extended states. The extended Kalman filter algorithm is employed to filter out the noise and adaptively adjust the tire model parameters. Then the final road longitudinal friction coefficient is accurately and robustly estimated. The Carsim simulation results show that the proposed method is better than the conventional algorithm. The road longitudinal friction coefficient can be quickly and accurately estimated under both the high and the low slip ratio conditions.The error is less than 0.1 and the response time is less than 2 s which meets the requirements of the vehicle longitudinal safety assistant system.

Application of nonlinear partial least square in catalyst modeling

The neural network partial least square (NNPLS) method was used to establish a robust reaction model for a multi-component catalyst of methane oxidative coupling. The details, including the learning algorithm, the number of hidden units of the inner network, activation function, initialization of the network weights and the principal components, are discussed. The results show that the structural organizations of inner neural network are 1-10-5-1, 1-8-4-1, 1-8-5-1, 1-7-4-1, 1-8-4-1, 1-8-6-1, respectively. The Levenberg-Marquardt method was used in the learning algorithm, and the central sigmoidal function is the activation function. Calculation results show that four principal components are convenient in the use of the multi-component catalyst modeling of methane oxidative coupling. Therefore a robust reaction model expressed by NNPLS succeeds in correlating the relations between elements in catalyst and catalytic reaction results. Compared with the direct network modeling, NNPLS model can be adjusted by experimental data and the calculation of the model is simpler and faster than that of the direct network model.

Characteristics for wind energy and wind turbines by considering vertical wind shear

The probability distributions of wind speeds and the availability of wind turbines were investigated by considering the vertical wind shear. Based on the wind speed data at the standard height observed at a wind farm, the power-law process was used to simulate the wind speeds at a hub height of 60 m. The Weibull and Rayleigh distributions were chosen to express the wind speeds at two different heights. The parameters in the model were estimated via the least square(LS) method and the maximum likelihood estimation(MLE) method, respectively. An adjusted MLE approach was also presented for parameter estimation. The main indices of wind energy characteristics were calculated based on observational wind speed data. A case study based on the data of Hexi area, Gansu Province of China was given. The results show that MLE method generally outperforms LS method for parameter estimation, and Weibull distribution is more appropriate to describe the wind speed at the hub height.

Notes on the Scaling Function

Two properties are given in this paper about the scaling function: suppose Vj; j ∈ Z is a multiresolution analysis with a continuous scaling function φ which have compact support set and that φ the Fourier transform of φ is a continuous real function, compactly supported, then φ(0) ≠ 0 and when supp φ = [a1,b1]∪[a2,b2](b1 < a2,0 < a2), then we havea1 ≤ 0, 0 < b1, a1 < b2/2 ≤ b1, 2π < b2 - a1 ≤ 8π.

Unknown parameter’s variance-covariance propagation and calculation in generalized nonlinear least squares problem

The unknown parameter’s variance-covariance propagation and calculation in the generalized nonlinear least squares remain to be studied now, which didn’t appear in the internal and external referencing documents. The unknown parameter’s vari- ance-covariance propagation formula, considering the two-power terms, was concluded used to evaluate the accuracy of unknown parameter estimators in the generalized nonlinear least squares problem. It is a new variance-covariance formula and opens up a new way to evaluate the accuracy when processing data which have the multi-source, multi-dimensional, multi-type, multi-time-state, different accuracy and nonlinearity.

Genetic algorithm-based evaluation of spatial straightness error

A genetic algorithm(GA)-based approach is proposed to evaluate the straightness error of spatial lines. According to the mathematical definition of spatial straightness, a verification model is established for straightness error, and the fitness function of GA is then given and the implementation techniques of the proposed algorithm is discussed in detail. The implementation techniques include real number encoding,adaptive variable range choosing, roulette wheel and elitist combination selection strategies,heuristic crossover and single point mutation schemes etc.An applicatin example is quoted to validate the proposed algorithm. The computation result shows that the GA-based approach is a superior nonlinear parallel optimization method. The performance of the evolution population can be improved through genetic operations such as reproduction,crossover and mutation until the optimum goal of the minimum zone solution is obtained. The quality of the solution is better and the efficiency of computation is higher than other methods.

2-D elastic wave modeling with frequency-space 25-point finite-difference operators

Numerical simulation in the frequency-space domain has inherent advantages, such as： it is possible to simulate wave propagation from multiple sources simultaneously; there are no cumulative errors; only the interesting frequencies can be selected; and it is more suitable for wave propagation in viscoelastic media. The only obstacle to using the method is the requirement of huge computer storage. We extend the compressed format for storing the coefficient matrix. It can reduce the required computer storage dramatically. We get the optimal coefficients by least-squares method to suppress the numerical dispersion and adopt the perfectly matched layer （PML） boundary conditions to eliminate the artificial boundary reflections. Using larger grid intervals decreases computer storage requirements and provides high computational efficiency. Numerical experiments demonstrate that these means are economic and effective, providing a good basis for elastic wave imaging and inversion.

Mixed-Weights Least-Squares Stable Predictive Control Algorithm with Soft and Hard Constraints

Mixed-weight least-squares (MWLS) predictive control algorithm, compared with quadratic programming (QP) method, has the advantages of reducing the computer burden, quick calculation speed and dealing with the case in which the optimization is infeasible. But it can only deal with soft constraints. In order to deal with hard constraints and guarantee feasibility, an improved algorithm is proposed by recalculating the setpoint according to the hard constraints before calculating the manipulated variable and MWLS algorithm is used to satisfy the requirement of soft constraints for the system with the input constraints and output constraints. The algorithm can not only guarantee stability of the system and zero steady state error, but also satisfy the hard constraints of input and output variables. The simulation results show the improved algorithm is feasible and effective.

A New Proposal to Adjust a Straight Line to a Normal Q-Q Plot

In this paper a new proposal of a straight line, the ＂modified Tukey＇s line＂, for fitting to a normal quantile-quantile Plot, or normal Q-Q plot, is presented. This probability plot allows us to determine whether a set of sample observations is distributed according to a normal distribution. For this, the sample quantiles are represented against the quantiles of a theoretical probability model, which in this case is the normal distribution. If the data set follows the above mentioned distribution, the plotted points will have a rectilinear configuration. To verify this, there are different alternatives for fitting a straight line to the plotted points. Among the straight lines which can be fitted to a Q-Q plot, in this paper, besides the proposed straight line, the following straight lines are considered： straight line that passes through the first and third quartiles, straight line that passes through the 10th and 90th percentiles, straight line fitted by the method of least squares, straight line with slope s and constant the average of the data set, Theil＇s line and Tukey＇s line. In addition, an example, in which there are represented the different straight lines considered and the proposed straight line on a normal Q-Q plot obtained for the same set of observations, is developed. In this example the existing differences among the straight lines are observed.

Quality prediction and control of tube hollow

The quality prediction of tube hollow model based on the variance staged multiway partial least square (MPLS) method was proposed.The key aspects of staged decomposition of the productive data,calculation of the variance value,modeling,and on-lined prediction in the variance-staged MPLS method were introduced.Based on the model,iterative optimal control method was used for quality control of tube hollow.The experimental results show that the obvious benefits of this method are low maintenance cost,good real time function,high reliability precision,and practical application to on-line prediction and optimization on the quality of tube hollow.

Novel robust approach for constructing Mamdani-type fuzzy system based on PRM and subtractive clustering algorithm

A novel approach for constructing robust Mamdani fuzzy system was proposed, which consisted of an efficiency robust estimator(partial robust M-regression, PRM) in the parameter learning phase of the initial fuzzy system, and an improved subtractive clustering algorithm in the fuzzy-rule-selecting phase. The weights obtained in PRM, which gives protection against noise and outliers, were incorporated into the potential measure of the subtractive cluster algorithm to enhance the robustness of the fuzzy rule cluster process, and a compact Mamdani-type fuzzy system was established after the parameters in the consequent parts of rules were re-estimated by partial least squares(PLS). The main characteristics of the new approach were its simplicity and ability to construct fuzzy system fast and robustly. Simulation and experiment results show that the proposed approach can achieve satisfactory results in various kinds of data domains with noise and outliers. Compared with D-SVD and ARRBFN, the proposed approach yields much fewer rules and less RMSE values.

Quantile Trends in Temperature Extremes in China

A number of recent studies have examined trends in extreme temperature indices using a linear regression model based on ordinary least-squares. In this study, quantile regression was, for the first time, applied to examine the trends not only in the mean but also in all parts of the distribution of several extreme temperature indices in China for the period 1960–2008. For China as a whole, the slopes in almost all the quantiles of the distribution showed a notable increase in the numbers of warm days and warm nights, and a significant decrease in the number of cool nights. These changes became much faster as the quantile increased. However, although the number of cool days exhibited a significant decrease in the mean trend estimated by classical linear regression, there was no obvious trend in the upper and lower quantiles. This finding suggests that examining the trends in different parts of the distribution of the time-series is of great importance. The spatial distribution of the trend in the 90 th quantile indicated that there was a pronounced increase in the numbers of warm days and warm nights, and a decrease in the number of cool nights for most of China, but especially in the northern and western parts of China, while there was no significant change for the number of cool days at almost all the stations.

Improved geologic surface approximation using a multiquadric method with additional constraints

Geologic surface approximation is profoundly affected by the presence, density and location of scattered geologic input data. Many studies have recognized the importance of utilizing varied sources of information when reconstructing a surface. This paper presents an improved geologic surface approximation method using a multiquadric function and borehole data. Additional information, i.e., inequality elevation and dip-strikes data extracted from outcrops or mining faces, is introduced in the form of physical constraints that control local changes in the estimated surface. Commonly accepted hypothesis states that geologic surfaces can be approximated to any desired degree of exactness by the summation of regular, mathematically defined, surfaces: in particular displaced quadric forms. The coefficients of the multiquadric functions are traditionally found by a least squares method. The addition of physical constraints in this work makes such an approach into a non-deterministic polynomial time problem. Hence we propose an objective function that represents the quality of the estimated surface and that includes the additional constraints by incorporation of a penalty function. Maximizing the smoothness of the estimated surface and its fitness to the additional constraints then allows the coefficients of the multiquadric function to be obtained by iterative methods. This method was implemented and demonstrated using data collected from the 81'st coal mining area of the Huaibei Coal Group.

Origin Distribution Patterns and Floating Population Modeling:Yiwu City as a Destination

Existing quantitative migration studies are mainly at the inter-region or inter-province level for lacking of detailed geo-referenced migration data.Meanwhile,few of them integrate explorative spatial data analysis and spatial regression model into migration analysis.Based on aggregated registered floating population data from 2005 to 2008,the phenomena that population floating to Yiwu City in Zhejiang Province is analyzed at the provincial and county levels.The spatial layout of Yiwu's pull forces is proved as a V-shaped pattern excluding Sichuan Province based on map visualization method.Using the migration ratio in 2007 as an explanatory variable,two models are compared using ordinary least square,spatial error model and spatial lag model methods for county-level data in Jiangxi and Anhui provinces.The model with migration stock provides an improved fitting over the model without migration stock according to the model fitting results.The floating population flocking into Yiwu City from Jiangxi is determined mostly by migration stock while the determinant factors are migration stock and distance to Yiwu City for Anhui.The distance-decay effect is true for migration flow from Anhui to Yiwu City while the distance rule is not confirmed in Jiangxi with the best fitting model.The correlation between per capita net income of rural labor forces and migration ratio is not significant in Jiangxi and significant but at the 0.1 level only in Anhui.Further analysis shows that the distance,income and man-land ratio are important factors to explain population floating at earlier stage.However,as the dynamic population floating process evolves,the determinant factor would be migration stock.

FMLSMETHODOFPARAMETERESTIMATIONANDITSAPPLICATIONTOHEAT┐EXCHANGERIDENTIFICATION

Using the inversion of the auto correlation function Toeplitz matrix of pseudo random binary sequence (PRBS) derived in this paper and the theorem of partitioned matrix inversion, a fast multistage least squares (FMLS) method is developed. Its performances are theoretically analyzed and digital simulation is made to compare FMLS with multistage least squares (MSLS), correlation least squares(COR LS) and LS for their computer speed and identification accuracy. Finally, FMLS is applied to identifying the heat excharger dynamics. It is shown that FMLS is a good and effective identification technique.

The Influence of Spiritual Values on Work Motivation, Management Control, and Quality of Financial Information on IFIs in Indonesia

This study aims to investigate the influence of spiritual values on work motivation, management control, and the quality of financial information on Islamic financial institutions （IFIs） in Indonesia. Spiritual values are measured using four reflexive indicators, namely, Shiddiq, Fathanah, Amanah, and Tabligh. Work motivation is formed by four formative indicators, namely, compensation, recognition, work experience, and openness. Management control variable is formed by four formative indicators, namely, planning, implementing, evaluating, and monitoring, and finally, the quality of financial information is manifested in four reflexive variables, namely, relevant, comparable, understandable, and consistent. Data are collected through questionnaires with 125 respondents as samples from three types of IFIs, such as Islamic banking, Islamic pawnshop, and Islamic insurance in Indonesia. Methods of data analysis include the use of partial least squares （PLS） to analyze the influence of spiritual values on work motivation, management control, and quality of financial information. The results of this study showed that the manifestation of spiritual values in IFIs is able to influence the quality of financial information through the media as motivation and management control, but directly spiritual values are not able to influence the quality of financial information. While work motivation and management control significantly influence the quality of financial information.

Accuracy Analysis of Geopotential Coefficients Recovered from In-situ Disturbing Potential by Energy Conservation Method

The characteristics of the normal equation created in recovering the Earth gravity model （EGM） by least-squares （LS） adjustment from the in-situ disturbing potential is discussed in detail. It can be concluded that the normal equation only depends on the orbit, and the choice of a priori gravity model has no effect on the LS solution. Therefore, the accuracy of the recovered gravity model can be accurately simulated. Starting from this point, four sets of disturbing potential along the orbit with different level of noise were simulated and were used to recover the EGM. The results show that on the current accuracy level of the accelerometer calibration, the accuracy of the EGM is not sufficient to reflect the time variability of the Earth＇s gravity field, as the dynamic method revealed.

PARAMETERIZATION OF TRIANGULAR MESHES

A new algorithm called the weighted least square discrete parameterization (WLSDP) is presented for the parameterization of triangular meshes over a convex planar region. This algorithm is the linear combination of the discrete Conformal mapping(DCM) and the discrete Authalic mapping(DAM). It provides the good properties of both DCM and DAM, such as robustness and low distortion. By adjusting the scaling factor q embedded in the WLSDP, satisfactory parameterizations in different special applications can be achieved.