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.

基于Curve Fitting Toolbox的普朗克常数测定

介绍了使用MATLAB曲线拟合工具箱(Curve Fitting Toolbox)对光电效应实验数据进行曲线拟合,并利用曲线拟合的结果计算得到了普朗克常数.结果显示,利用曲线拟合工具箱能方便、直观的对实验数据进行拟合,使得实验的数据处理过程方便、准确.

Study on curved surface fitting model using GPS and leveling in local area

The height anomaly surface is fitt and the quasi-geoid can be obtained when the height anomaly is determined with the geometric analytic method. Therefore, some mathematical models to fit height anomaly surface using GPS, leveling and terrain data in a local area, including the polynomial fitting model, the multi-surface function fitting model, the motion surface fitting model and the fitting model of little flexibility deformation of thin board, are given. Then the digital characteristics are analyzed with the curved surface theory. The General curvature and the mean curvature of surface are concluded. The advantage, disadvantage and application of the above models are discussed. The effect of terrain undulation on height anomaly is considered in the surface fitting models. The practical case indicates that these models are of validity and practicability. It is concluded that the above models can give the good fitting results at the centimeter level. But the polynomial fitting model is worse than the other models.

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.

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.

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.

Evaluating instrumented Charpy impact strain signals using curve fitting equations

An effective and simple way to develop equations from impact strain signals was proposed.Little research has been performed in this area,but this equation is very important for evaluating input signals in finite element analysis impact tests and for obtaining additional information on material deformation and fracture processes under impact loading.For this purpose,dynamic impact responses were examined through signals obtained from a strain gauge installed on an impact striker connected to a data acquisition system.Aluminium 6061-T6 was used to extract strain responses on the striker during Charpy impact testing.Statistical analysis was performed using the I-kaz method,and curve fitting equations based on the equation for vibration response under a non-periodic force were used to evaluate the Charpy impact signals.The I-kaz coefficients and curve fitting equations were then compared and discussed with related parameters,such as velocities and thicknesses.Velocity and thickness were found to be related to the strain signal patterns,curve fitting equations and I-kaz coefficients.The equations developed using this method had R2 values greater than 97.7%.Finally,the constructed equations were determined to be suitable for evaluating Charpy impact strain signal patterns and obtaining additional information on fracture processes under impact loading.

A NEW APPROACH TO THE CURVE FITTING OF IN VITRO RADIOASSAYS BASED ON THE MASS ACTION LOW

A new curve fitting method with its mathematical models derived from the mass action law is presented which is applicable to several in vitro radioassays including RIA and RBA. Experiments revealed that the robustness of this method is better than the conventional methods like Woolf plot in RBA and 4- parameter logistic plot in RIA. However, the robustness of this method is only relative: in some cases of RIA and RBA, the bias of the results may still be too large to be acceptable. Further improvement is expected to be studied.

Microwave method based on curve fitting method for high-precision collision frequency diagnosis

In this work,the results of plasma microwave transmission diagnosis were analyzed.According to the attenuation and phase shift of the electromagnetic wave propagating in the plasma,the electron density and collision frequency of the plasma can be diagnosed.Since part of the electromagnetic wave is reflected or diffracted when propagating in the plasma,and is not absorbed by the plasma,and this part of the attenuation is still included in the measured attenuation,the attenuation is distorted.Therefore,a curve fitting method is proposed to remove the attenuation caused by the plasma reflection,thereby improving the accuracy of the diagnosis of the collision frequency.The calibration effect of this method on plasmas with different electron densities and collision frequencies is analyzed,and a diagnostic frequency band with good calibration results is given.The curve fitting method is verified by experiment and simulation.After adopting the newly proposed method,the diagnosis accuracy of collision frequency can be increased by 30%.This method can be widely used in various types of plasma diagnosis and provides a new idea for plasma diagnosis.

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.

Arm-Root Curve Fitting Based on Body Surface Feature Points for Young Male

This paper is aiming to obtain an arm-root curve function performing the human arm-root size and shape realistically. A gypsum replica of upper arm for young male was made and scanned for extracting the 3D coordinates of 4 feature points of shoulder point, the anterior/posterior armpit point and the axillary point describing the real arm-root shape under the normalized definitions, and the 5 landmarks were confirmed additionally for improving the fitting precision. Then, the wholly and piecewise fitting of arm-root curve with 9 feature points and mark points in total were generated respectively based on least square polynomial fitting method. Comparing to the wholly fitting, the piecewise fitted function segmented by the line between anterior and posterior axillary points showed a high fitting degree of arm-root morphology with R-square of 1, the length difference between fitted curve and gypsum curve is 0.003 cm within error range. And it provided a basic curve model with standard feature points to simulate arm-root morphology realistically by curve fitting for accurate body measurement extraction.

FTIR Study of White and Green Broad Beans Based on Curve-fitting

Fourier transform infrared(FTIR)spectroscopy was used to study two kinds of broad beans with white and green cotyledons respectively.The results show that the infrared spectra of the two kinds of broad beans are similar and mainly made up of the absorption bands of protein,and polysaccharides.The second derivative infrared spectra amplified the differences and revealed that there were some obvious differences in the range of 1 800-700 cm-1and 1 200-700 cm-1.Hierarchical cluster analysis(HCA)were used for the discrimination of the two kinds broad beans based on the second derivative spectral data in the region of 1 611-1 100 cm-1,and yielded 88.9%accuracy.The spectra in the range from 1 700 to 1 600 cm-1were used to perform Fourier self-deconvolution and curve fitting,which obtained nine peaks.The ratios of relative areas of the bands atα-helix,β-sheet,β-turn and the unordered structure of protein in white beans were 67.71%,35.6%,35.6%and 21.09%respectively,while the ratios in green beans were 8.02%,31.59%,37.12%and 23.27%respectively.The results indicate that the secondary structure of protein was different in the two kinds of broad beans.

Predicting of Land Surface Temperature Distribution in Freetown City, Sierra Leone by Using Polynomial Curve Fitting Model

Global warming has attracted much concern about the worldwide organization, civil society groups, researchers, and so forth because the worldwide surface temperature has been expanding. This investigation intends to assess and compare the ability of a combination of land cover indices to predict the future distribution of land surface temperatures in Freetown using the Polynomial model analysis. Landsat satellite images of 1988, 1998, 2000, 2010, and 2018 of the Freetown Metropolitan zone were utilized for analysis. The investigation had adopted two land covers indices, Modification of normalized difference water index and Urban Index (UI) (e.g., MNDWI and UI) and applied a multi regression equation for forecasting the future LST. The stimulation results propose that the development will be accompanied by surface temperature increases, especially in Freetown’s western urban area. The temperature prevailing in the west of the metropolitan area may increase in the city somewhere in the range from 1988 to 2018. Additionally, the results of the LST prediction show that the model is perfect. Our discoveries can be represented as a helpful device for policymakers and community awareness by giving a scientific basis for sustainable urban planning and management.

Age-Structured Population Projection of Bangladesh by Using a Partial Differential Model with Quadratic Polynomial Curve Fitting

In this paper, the age-specific population of Bangladesh based on a linear first order (hyperbolic) partial differential equation which is known as Von-Foerster Equation is studied. Applying quadratic polynomial curve fitting, the total population and population density of Bangladesh are projected for the years 2001 to 2050 based on the explicit upwind finite difference scheme for the age-structured population model based on given data (source: BBS & ICDDR, B) for initial value in the year 2001. For each age-group, the future birth rates and death rates are estimated by using quadratic polynomial curve fitting of the data for the years 2001 to 2012. Quadratic polynomial curve fitting is also used for the boundary value as the (0 - 4) age-group population based on the population size of the age-group for the years 2001 to 2012.

Separating Overlapped Peaks of SF6 Decomposed Products Based on Iterative Curve-fitting Method

The SF6 decomposed products are very alike,so the peaks of the SF6 decomposed products are overlapped.It make us hard to quantitatively calculate.This paper introduced a method to separate the overlapped chromatogram peaks with iterative curve-fitting and Gauss function,and deduced the formula of the iterative curve-fitting;provided a method to calculate the initial value of the peaks intensity and width by iterative formula,and confirm the final peaks intensity and width to separate the overlapped signals.By the analysis of the real chromatogram data,it proved the validity of this method on the main components used in distinguishing the GIS internal defects.This method overcomes the influence of SF6 peak to the other thin concentration peaks,so it can be used in the study of the quantitative analysis of the decomposed products on different failures and different voltages.

NON-STATIONARY SIGNAL DENOISING USING TIME-FREQUENCY CURVE SURFACE FITTING

Based on the theory of adaptive time-frequency decomposition and Time-Frequency Dis- tribution Series (TFDS), this paper presents a novel denoising method for non-stationary signal. Ac- cording to the input signal features, an appropriate kind of elementary functions with great concen- tration in the Time-Frequency (TF) plane is selected. Then the input signal is decomposed into a linear combination of these functions. The elementary function parameters are determined by using ele- mentary function TF curve surface to fit the input signal’s TFDS. The process of curved surface fitting corresponds to the signal structure matching process. The input signal’s dominating component whose structure has the resemblance with elementary function is fitted out firstly. Repeating the fitting process, the residue can be regarded as noises, which are greatly different from the function. Selecting the functions fitted out initially for reconstruction, the denoised signal is obtained. The performance of the proposed method is assessed by means of several tests on an emulated signal and a gearbox vi- brating signal.

Curve Fitting in Analyzing the Menstrual Irregularities afterImplantation of Norplant

This paper presents the menstrual disorders produced by implantation of Norplantin women during a course of five-year usage. Total 1000 women were recruited. Themain side thects consisted of changes in bleeding patterns, including: menostaxis, hxpomenorrhoea, spotting,frequent menstruation, lnfrequent menstruation, amenorrhoeaand menorrhagia. Authors of this paper suggested that all the above-mentioned men-strual disorders could be explained by mathematical methods. Except for the incidenceof menorrhagia which revealed a negative linear correlation with the implantation timeinterval (correiation coefficient is - 0. 98), all the other six patterns of the abnormalbleeding changes could be fitted by the hyperbola model, because their incidencesreached a very high value in 3~ 6 months after implantation, then sharply dropped toa lower value at the end of one year, whence in turn were reduced slowly but progres-sively to the the end of the 5 th year. The results of all F tests were statistically signWicant (P< 0.01). The advantages of this curve fitting method are: 1, to show the re-lationships between the mismenstruational rates and time afer implantation of Norplant at a theoretical level; 2, to make a direct image; 3, tosmooth the values of the ob-servation and decrease the sampling variation; 4, to estimate the incidences of mismen-struation at a given time; 5, to tell women the changing rule of mismenstruations anddeveloping prospect before and after the implantation in order to increase their confi-dence and meanwhile to increase the conlinuous using rate.

Analysis Approach to Durability Based on Material Initial Fatigue Quality and S-N Curve

Based on probabilistic fracture mechanics approach, a new concept of material initial fatigue quality （MIFQ） is developed. Then, the relation between S-N curve and crack propagation curve is studied. From the study, a new durability analysis method is presented. In this method, S-N curve is used to determine crack growth rate under constant amplitude loading and evaluate the effects of different factors on durability and then the structural durability is analyzed. The tests and analyses indicate that this method has lower dependence on testing, and higher accuracy, reliability and generality and is convenient for application.