WEIGHTED LEAST SQUARE METHOD FOR S-N CURVE FITTING

An S-N curve fitting approach is proposed based on the weighted least square method, and the weights are inversely proportional to the length of mean confidence intervals of experimental data sets. The assumption coincides with the physical characteristics of the fatigue life scatter. Two examples demonstrate the method. It is shown that the method has better accuracy and reasonableness compared with the usual least square method.

Curve Fitting and Least Square Analysis to Extrapolate for the Case of COVID-19 Status in Ethiopia

On 30 January 2020 World Health Organization (WHO), declared the novel corona virus as a Public Health Emergency of International Concern (PHEIC), COVID-19 virus as an epidemic transmitted virus. It was on 31 December 2019, the WHO China Country office was informed the cases of pneumonia unknown etiology detected in Wuhan city, Hubei Province of China. Just after WHO’s declaration, Ethiopia has taken different measures to protect from this public health emergency problem. The disease is human to human transmitted virus. It comes from outside of the country, so that it opens check points in different entrance of the country. However, in 13 March 2020 the first positive case was reported from Japanese man. The virus is continuing the transmission in the public progressively more. While this research has been working, within 90 days from the first case, the country reported 2506 positive cases, 35 deaths. The research has done after collecting the first 90 days of data in Ethiopian case. Daily report announced by Ethiopian MoH is based on the test. And hence, the reported data as positive cases with COVID-19 is not actual positive case data in the country. There for, this paper has contribution for planning and taking further measure on the viruses by demonstrating the next 90 days predictive data. I use best curve fitting analysis using python function of the module polyfit algorithm to predict the trend of COVID-19 cases in Ethiopia.

Comparative Analysis of Equal and Unequal Grounding Grid Configurations by Compression Ratio and Least Square Curve Fitting Techniques

The primary aim of the power system grounding is to safeguard the person and satisfying the performance of the power systemtomaintain reliable operation.With equal conductor spacing grounding grid design,the distribution of the current in the grid is not uniform.Hence,unequal grid conductor span in which grid conductors are concentrated more at the periphery is safer to practice than equal spacing.This paper presents the comparative analysis of two novel techniques that create unequal spacing among the grid conductors:the least-square curve fitting technique and the compression ratio techniquewith equal grid configuration for both square and rectangular grids.Particle Swarm Optimization(PSO)is adopted for finding out one optimal feasible solution among many feasible solutions of equal grid configuration for both square and rectangular grids.Comparative analysis is also carried out between square and rectangular grids using the least square curve fitting technique as it results in only one unequal grid configuration.Simulation results are obtained by theMATLAB software developed.Percentage of improvement in ground potential rise,step voltage,touch voltage,and grid resistancewith variation in compression ratios are plotted.

Study on Growth and Development Rules and Growth Curve Fitting of Minghua Black Minks

Growth curves of Minghua black minks at 0-180 days old were fitted and analyzed by using two growth models Logistic and Gompertz. The results showed that the growth curves of Minghua black minks could be fitted very well by Logistic model and Gompertz model （the degree of fitting FF≥0.99）, but Gompertz model was better at fitting and predicting their weight.

Comparative Study on Analysis and Fitting of Pudong Chicken Growth Curve

The objective of this paper was to study the growth and development laws of Pudong chicken. The growth curve of Pudong chicken （cock and hen） from 0 to 20 weeks was analyzed and fitted with three models（Gompertz, Logistic and Bertalanffy）. It was concluded that the growth curves were appropriately fitted with three models, and fitness degree （R2）in growth data of Pudong chicken were all above 0.992. The Bertalanffy model was the most effective with the highest R2 for cock （R^2=0.995） and hen （R^2=0.999）, respectively. With further analysis of fitted parameters for Logis- tic model of cock, 0-3 weeks＇ fitted values were significantly greater than measured values and 4-8 weeks＇ fitted values were lower than measured values. Compared with Logistic model, the values calculated by Gompertz model and Bertalanffy model were more coincident with the practical measuring values. For hens, 0-3 weeks＇ fitted values of Logistic model were significantly greater than measured values and 0-2 weeks＇ fitted values of Gompertz model were slightly greater than measured values, while the values calculated by Bertalanffy model best matched the observed values from actual measure. The results showed that Bertalanffy model used to estimate the growth weight of Pudong chicken was the best while Logistic model was the worst. So the fitness and analysis of growth curves of Pudong chicken are valid, which may be adopted to predict growth and development laws of Pudong chicken and provide reliable data for precise feeding and breeding.

Penalized total least squares method for dealing with systematic errors in partial EIV model and its precision estimation

When the total least squares(TLS)solution is used to solve the parameters in the errors-in-variables(EIV)model,the obtained parameter estimations will be unreliable in the observations containing systematic errors.To solve this problem,we propose to add the nonparametric part(systematic errors)to the partial EIV model,and build the partial EIV model to weaken the influence of systematic errors.Then,having rewritten the model as a nonlinear model,we derive the formula of parameter estimations based on the penalized total least squares criterion.Furthermore,based on the second-order approximation method of precision estimation,we derive the second-order bias and covariance of parameter estimations and calculate the mean square error(MSE).Aiming at the selection of the smoothing factor,we propose to use the U curve method.The experiments show that the proposed method can mitigate the influence of systematic errors to a certain extent compared with the traditional method and get more reliable parameter estimations and its precision information,which validates the feasibility and effectiveness of the proposed method.

Energy-Minimizing Curve Fitting for High-Order Surface Mesh Generation

We investigate different techniques for fitting Bézier curves to surfaces in context of high-order curvilinear mesh generation. Starting from distance-based least-squares fitting we develop an incremental algorithm, which incorporates approximations of stretch and bending energy. In the process, the algorithm reduces the energy weight in favor of accuracy, leading to an optimized set of sampling points. This energy-minimizing fitting strategy is applied to analytically defined as well as triangulated surfaces. The results confirm that the proposed method straightens and shortens the curves efficiently. Moreover the method preserves the accuracy and convergence behavior of distance-based fitting. Preliminary application to surface mesh generation shows a remarkable improvement of patch quality in high curvature regions.

Least squares fitting of coordinate parameters model

This paper starts with untime-diversification of the time-diversification deformation model and gives displacement distribution model of untime-diversification and simplifies further the study of deformation model. The paper discusses the problem of least squares fitting of coordinate parameters model—parameters of deformation model. During discussion, the basic means of cubic B splines and two steps of multidimensional disorder datum fitting are adopted which can make fitting function calculated mostly approximate coordinate parameters model and it can make calculation easier.

Study on Coal Consumption Curve Fitting of the Thermal Power Based on Genetic Algorithm

Coal consumption curve of the thermal power plant can reflect the function relationship between the coal consumption of unit and load, which plays a key role for research on unit economic operation and load optimal dispatch. Now get coal consumption curve is generally obtained by least square method, but which are static curve and these curves remain unchanged for a long time, and make them are incompatible with the actual operation situation of the unit. Furthermore, coal consumption has the characteristics of typical nonlinear and time varying, sometimes the least square method does not work for nonlinear complex problems. For these problems, a method of coal consumption curve fitting of the thermal power plant units based on genetic algorithm is proposed. The residual analysis method is used for data detection;quadratic function is employed to the objective function;appropriate parameters such as initial population size, crossover rate and mutation rate are set;the unit’s actual coal consumption curves are fitted, and comparing the proposed method with least squares method, the results indicate that fitting effect of the former is better than the latter, and further indicate that the proposed method to do curve fitting can best approximate known data in a certain significance, and they can real-timely reflect the interdependence between power output and coal consumption.

A SPACE THEORY BASIS FOR CURVE FITTING PROBLEMS

itherto, a precision Concept for curve fitting problems has not been set. By using the theory of functional analysis, the author of this paper established a space theory basis for curve fitting problems. Also given in the paper is the precision concept of the curve fitting problems and the method for constructing the fitting of a curve satisfying given precision requirements.

Establishment and Analysis of Growth Curve of Muchuan Black Chicken

To find out the growth and development regularity,the growth curves of Muchuan black chicken at the age of 0-21 weeks were established by Logistic,Bertalanffy and Gompertz models in this study.The results showed that all the three models can well fit the growth curve of Muchuan black chicken with a degree above 0.988,while the Gompertz model and the Bertalanffy model was the best for hens and cocks,respectively.Finally,the weight of hens and cocks were analyzed according to their corresponding high fitting models.Results showed that the inflexion age of Muchuan black chicken was 6.8-6.9 weeks old with an inflexion weight of 692.98 g in hens and 805.57 g in cocks.In conclusion,it was feasible to establish the growth curve of Muchuan black chicken with Logistic,Bertalanffy and Gompertz model.

Weight-based shape modification of NURBS curves by constrained optimization

A new method for shape modification of non-uniform rational B-splines (NURBS) curves was presented, which was based on constrained optimization by means of altering the corresponding weights of their control points. Using this method, the original NURBS curve was modified to satisfy the specified geometric constraints, including single point and multi-point constraints. With the introduction of free parameters, the shapes of modified NURBS curves could be further controlled by users without destroying geometric constraints and seem more naturally. Since explicit formulae were derived to compute new weights of the modified curve, the method was simple and easy to program. Practical examples showed that the method was applicable for computer aided design (CAD) system.

Statistical Analysis Methods of Fatigue Crack Growth Rate

The standard center-cracked tensile specimens M （T） with different widths made of aluminum alloy were designed for fatigue crack growth rate experiments, and the effect of specimen size on the fatigue crack growth rate was discussed. The firing equation and the p-da/dN-△K curve of fatigue crack growth rate （with different confidence and reliability levels） were obtained by one-side tolerance factor analysis. In order to reasonably reflect the dispersion of material properties on the fatigue crack growth rate and fatigue crack propagation life, two novel statistical analysis methods were proposed, which can be used to describe the probability distribution of fatigue crack growth rate. Compared with the traditional statistical analysis method of probabilistic fatigue crack growth rate, the fitted curves from the novel statistical analysis methods yield more objective description on the probability distribution of crack growth rate.

Perturbation Analysis of Structured Least Squares Problems and Its Application in Calibration of Interest Rate Term Structure

A structured perturbation analysis of the least squares problem is considered in this paper.The new error bound proves to be sharper than that for general perturbations. We apply the new error bound to study sensitivity of changing the knots for curve fitting of interest rate term structure by cubic spline.Numerical experiments are given to illustrate the sharpness of this bound.

A CONCISE M-METRIC LEAST SQUARE FORMULA FOR POLYNOMIAL ANALOGY

An M-metric least square method for polynomial analogy is presented. The relative normal eqUation is of diagonal form, such that the concise solution formula is explicit, and it is suitable to Parallel computation. On the other hand, by error analysis of a typical example, we can see that the presented method is reliable.

ON CURVED SURFACE APPROXIMATION AND HIDDEN SURFACE ELIMINATION IN 3-D COMPUTER AIDED GARMENT DESIGN

An approximation method for curved surface mannequin and hidden surface eliminationin 3-D computer aided garment design system is described. The mannequin is the basis of the3-D modeling for clothes. In terms of the requirements of computer aided garment design,the authors put forward a method for curved surface approximation in the meaning of leastsquares. Using. this method the computation of geometric modeling is simple andefficient. It is also convenient for curved surface modification and shading.

Design of Ballistic Consistency Based on Least Squares Support Vector Machine and Particle Swarm Optimization

In order to improve the firing efficiency of projectiles,it is required to use the universal firing table for gun weapon system equipped with a variety of projectiles.Moreover,the foundation of sharing the universal firing table is the ballistic matching for two types of projectiles.Therefore,a method is proposed in the process of designing new type of projectile.The least squares support vector machine is utilized to build the ballistic trajectory model of the original projectile,thus it is viable to compare the two trajectories.Then the particle swarm optimization is applied to find the combination of trajectory parameters which meet the criterion of ballistic matching best.Finally,examples show the proposed method is valid and feasible.

Rail Detection Based on LSD and the Least Square Curve Fitting

It is necessary to rely on the rail gauge to determine whether the object beside the track will affect train operation safety or not.A convenient and fast method based on line segment detector(LSD)and the least square curve fitting to identify the rail in the image is proposed in this paper.The image in front of the train can be obtained through the camera on-board.After preprocessing,it will be divided equally along the longitudinal axis.Utilizing the characteristics of the LSD algorithm,the edges are approximated into multiple line segments.After screening the terminals of the line segments,it can generate the mathematical model of the rail in the image based on the least square.Experiments show that the algorithm in this paper can fit the rail curve accurately and has good applicability and robustness.

Rhizome Elongation Growth of Umbrella Bamboo(Fargesia murielae) Seedlings at Its Native Home in Central China

[Objective] The aim was to investigate the rhizome elongation growth of umbrella bamboo （Fargesia murielae） seedlings in China. [Method] The study was conducted in Liangfengya, Shennongjia National Nature Reserve. In the field investigation, six clumps of umbrella bamboo which grow independently were randomly selected and labeled. Rhizome elongation growth parameters, length and diameter of all the ages were measured. The age classes of bamboo rhizome were ascertained by age grade backtracking method. [Result] Field investigation suggested that at seedling phase, rhizome of umbrella bamboo prolonged very quickly under yearly time sequence, following an exponential curve. It indicated that although it was 15 years since the mother population died back, new generation had not been established its stable population yet. [Conclusion] Studying elongation regulation of umbrella bamboo may provide the theory understanding of life cycle of this long lived bamboo species.

Science Letters:Evaluation of a kinetic uricase method for serum uric acid assay by predicting background absorbance of uricase reaction solution with an integrated method

A patented kinetic uricase method was evaluated for serum uric acid assay. Initial absorbance of the reaction mixture before uricase action （A0） was obtained by correcting the absorbance at 293 nm measured before the addition of uricase solution, and background absorbance （Ab） was predicted by an integrated method. Uric acid concentration in reaction solution was calculated from AA, the difference between A0 and Ab, using the absorptivity preset for uric acid. This kinetic uricase method exhibited CV〈4.3% and recovery of 100%. Lipids, bilirubin, hemoglobin, ascorbic acid, reduced glutathione and xanthine 〈0.32 mmol/L in serum had no significant effects. △A linearly responded to 1.2 to 37.5 μmol/L uric acid in reaction solution containing 15 μl serum. The slope of linear response was consistent with the absorptivity preset for uric acid while the intercept was consistent with that for serum alone. Uric acid concentrations in clinic sera by different uricase methods positively correlated to each other. By Bland-Altman analysis, this kinetic uricase method accorded with that by quantifying the total change of UV absorbance on the completion of uricase reaction. These results demonstrated that this kinetic uricase method is reliable for serum uric acid assay with enhanced resistance to both xanthine and other common errors, wider range of linear response and much lower cost.