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Journal articles on the topic 'Distribution analysis method'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

DEBBAL, S. M. "Heart Cardiac Sounds analysis using the Wigner distribution (WD) Method." Clinical Cardiology and Cardiovascular Interventions 04, no. 15 (September 20, 2021): 01–04. http://dx.doi.org/10.31579/2641-0419/216.

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This paper is concerned a “The Wigner distribution (WD)” analysis of the Heart cardiac (or phonocardiogram signals: PCG). The Wigner distribution (WD) and the corresponding WVD (Wigner Ville Distribution) have shown good performances in the analysis of non-stationary and quantitative measurements of the time-frequency PCG signal characteristics. It is shown that these transforms provides enough features of the PCG signals that will help clinics to obtain diagnosis.

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Li Wei, Li Wei, and Bing-Wu Fang Li Wei. "Safety Analysis Method of Mixed Failure Model using Temporal Bayesian Network." 網際網路技術學刊 23, no. 4 (July 2022): 727–34. http://dx.doi.org/10.53106/160792642022072304008.

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<p>Dynamic Fault Tree (DFT) is used widely in the community of reliability and safety analysis of a complex system. DFT is a high-level modeling language lacking formal semantics, so we need to convert it to a mathematical model to analyze. The conventional analysis method can only solve the DFT with discrete or exponential distribution, but not the DFT with mixed distributions. To this end, we first propose a TBN framework to represent the DFT with mixed failure distribution by extending the BN and introduce Dirac delta functions and unit-step functions into the framework to represent the logical relationship and temporal relationship between the nodes, respectively. To run the standard BN inference algorithm over TBN, we fit the failure distribution of the nodes by using k-piece and n-degree polynomials. We then propose a transformation method from DFT to TBN and prove the equivalence of the transformation. Finally, the analysis of the DFT model of the X2000 avionics system shows that our approach can effectively analyze the reliability of mixed distribution failure models. Moreover, the accuracy and efficiency of the analysis are significantly better than current mainstream methods.</p> <p> </p>

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3

LIU, S. G., P. WANG, and Z. G. LI. "NON-NORMAL STATISTICAL TOLERANCE ANALYSIS USING ANALYTICAL CONVOLUTION METHOD." Journal of Advanced Manufacturing Systems 07, no. 01 (June 2008): 127–30. http://dx.doi.org/10.1142/s0219686708001218.

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In statistical tolerance analysis, it is usually assumed that the statistical tolerance is normally distributed. But in practice, there are many non-normal distributions, such as uniform distribution, triangular distribution, etc. The simple way to analyze non-normal distributions is to approximately represent it with normal distribution, but the accuracy is low. Monte-Carlo simulation can analyze non-normal distributions with higher accuracy, but is time consuming. Convolution method is an accurate method to analyze statistical tolerance, but there are few reported works about it because of the difficulty. In this paper, analytical convolution is used to analyze non-normal distribution, and the probability density functions of closed loop component are obtained. Comparing with other methods, convolution method is accurate and faster.

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Guo, Li, Mingqing Liu, Ronghua Lu, Shensheng Han, and Jing Chen. "Analysis of above-threshold ionization by “Wigner-distribution-like function” method." Laser and Particle Beams 37, no. 4 (September 18, 2019): 448–62. http://dx.doi.org/10.1017/s0263034619000569.

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AbstractAbove-threshold ionization (ATI) is one of the most fundamental processess when atoms or molecules are subjected to intense laser fields. Analysis of ATI process in intense laser fields by a Wigner-distribution-like (WDL) function is reviewed in this paper. The WDL function is used to obtain various time-related distributions, such as time-energy distribution, ionization time distribution, and time-emission angle distribution and so on, of atoms in laser field pulses with different laser parameters. For the linearly polarized laser pulses, the time-energy distribution intuitively shows from a quantum point of view the relationship between the ionization moment and the final energy and clearly reveals the origin of interference structures in the photoelectron spectrum. In particular, for linearly polarized few-cycle laser pulses, all calculated distributions show the dependence of electron behavior on the ionization time, emission direction, and carrier-envelope phase (CEP). For elliptically polarized few-cycle pulses, we calculate the angular distribution, ionization time distribution, and time-emission distribution, which are compared with the semiclassical calculations. Analysis shows that the offset angle (difference between positions of the peaks in the angular distributions obtained by two methods) in the angular distributions does not correspond to the offset time (difference between positions of the peaks in the ionization time distributions obtained by two methods) in the ionization time distributions, which implies that the attosecond angular streaking technique based on this correspondence between the offset angle and time is in principle inaccurate. Furthermore, the offset time cannot be interpreted as tunneling time.

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Zhang, Peng, Qian Yu, Yuexian Hou, Dawei Song, Jingfei Li, and Bin Hu. "Generalized Analysis of a Distribution Separation Method." Entropy 18, no. 4 (April 13, 2016): 105. http://dx.doi.org/10.3390/e18040105.

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6

Zhang, YL, and YM Zhang. "A new stochastic analysis method for mechanical components." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 227, no. 8 (November 23, 2012): 1818–29. http://dx.doi.org/10.1177/0954406212467735.

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Univariate dimension-reduction integration, maximum entropy principle, and finite element method are employed to present a computational procedure for estimating probability densities and distributions of stochastic responses of structures. The proposed procedure can be described as follows: 1. Choose input variables and corresponding distributions. 2. Calculate the integration points and perform finite element analysis. 3. Calculate the first four moments of structural responses by univariate dimension-reduction integration. 4. Estimate probability density function and cumulative distribution function of responses by maximum entropy principle. Numerical integration formulas are obtained for non-normal distributions. The non-normal input variables need not to be transformed into equivalent normal ones. Three numerical examples involving explicit performance functions and solid mechanic problems without explicit performance functions are used to illustrate the proposed procedure. Accuracy and efficiency of the proposed procedure are demonstrated by comparisons of the estimated probability density functions and cumulative distribution functions obtained by maximum entropy principle and Monte Carlo simulation.

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Simanavičienė, Rūta, and Vaida Petraitytė. "Sensitivity Analysis of the TOPSIS Method in Respect of Initial Data Distributions." Lietuvos statistikos darbai 55, no. 1 (December 20, 2016): 45–51. http://dx.doi.org/10.15388/ljs.2016.13866.

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The present article investigates the sensitivity of the multiple criteria decision-making method TOPSIS in respectof attribute probability distributions. To carry out research, initial data – attribute values – were generated according to anormal, log-normal, uniform, and beta distributions. Decision matrixes were constructed from the generated data. Byapplying the TOPSIS method to the matrixes generated, result samples were received. A statistical analysis was conductedfor the results obtained, which revealed that the distributions of the initial data comply with the distributions of the resultsreceived by the TOPSIS method. According to the most common alternative rank value, it was ascertained that the TOPSISmethod is the most sensitive for data distribution according to beta distribution, and the least sensitive for data distributionaccording to lognormal distribution.

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8

Cespedes, R. G. "New method for the analysis of distribution networks." IEEE Transactions on Power Delivery 5, no. 1 (1990): 391–96. http://dx.doi.org/10.1109/61.107303.

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9

Spiliotis, M., and G. Tsakiris. "Water Distribution System Analysis: Newton-Raphson Method Revisited." Journal of Hydraulic Engineering 137, no. 8 (August 2011): 852–55. http://dx.doi.org/10.1061/(asce)hy.1943-7900.0000364.

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10

Matsuo, Munetsugu, Koichi Kawasaki, and Tetsuya Sugai. "A New Method for Orientation Distribution Function Analysis." Advances in X-ray Analysis 29 (1985): 443–49. http://dx.doi.org/10.1154/s0376030800010569.

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AbstractAs a means for quantitative texture analysis, the crystallite orientation distribution function analysis has an important drawback: to bring ghosts as a consequence of the presence of a non-trivial kernel which consists of the spherical harmonics of odd order terms. In the spherical hamonic analysis, ghosts occur in the particular orientations by symmetry operation from the real orientation in accordance with the symmetry of the harmonics of even orders. For recovery of the odd order harmonics, the 9th-order generalized spherical harmonics are linearly combined and added to the orientation distribution function reconstructed from pole figures to a composite function. The coefficients of the linear combination are optimized to minimize the sum of negative values in the composite function. Reproducibility was simulated by using artificial pole figures of single or multiple component textures. Elimination of the ghosts is accompanied by increase in the height of real peak in the composite function of a single preferred orientation. Relative fractions of both major and minor textural components are reproduced with satisfactory fidelity In the simulation for analysis of multi-component textures.

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11

Bollen, M. H. J. "Method for reliability analysis of industrial distribution systems." IEE Proceedings C Generation, Transmission and Distribution 140, no. 6 (1993): 497. http://dx.doi.org/10.1049/ip-c.1993.0072.

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12

Wen, Juan, Yanghong Tan, and Kejun Lei. "A Dynamic Topology Analysis Method in Distribution Systems." Journal of Computational and Theoretical Nanoscience 13, no. 11 (November 1, 2016): 8544–51. http://dx.doi.org/10.1166/jctn.2016.6009.

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13

Kim, Dohoon. "Potential Risk Analysis Method for Malware Distribution Networks." IEEE Access 7 (2019): 185157–67. http://dx.doi.org/10.1109/access.2019.2960552.

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14

Sorin, M., and J. Paris. "Integrated exergy load distribution method and pinch analysis." Computers & Chemical Engineering 23, no. 4-5 (May 1999): 497–507. http://dx.doi.org/10.1016/s0098-1354(98)00288-9.

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15

Zhen-Rong, Liu, and Huang Chong-Fu. "Information distribution method relevant in fuzzy information analysis." Fuzzy Sets and Systems 36, no. 1 (May 1990): 67–76. http://dx.doi.org/10.1016/0165-0114(90)90079-l.

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16

Akiba, Hiroshi, and Genki Yagawa. "Recursive distribution method for probabilistic structural integrity analysis." Computer Methods in Applied Mechanics and Engineering 168, no. 1-4 (January 1999): 135–54. http://dx.doi.org/10.1016/s0045-7825(98)00099-1.

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17

Záboj, M. "Analysis of using the Category Management in distribution process." Agricultural Economics (Zemědělská ekonomika) 50, No. 9 (February 24, 2012): 423–28. http://dx.doi.org/10.17221/5228-agricecon.

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The paper deals with the very actual sphere of new conceptions in frame of supplier-customer relations between trade firms and their suppliers. The common idea is management of the distribution channel by the method it would create consumer feeling that the retail shop satisfies his wants and gives him the greatest benefit with the most favourable price. Presumption for realisation of this goal becomes the implementation of a new phenomenon, so-called “Category Management” to current business processes using modern information technology.

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18

Tian, Weizhong, Liyuan Pang, Chengliang Tian, and Wei Ning. "Change Point Analysis for Kumaraswamy Distribution." Mathematics 11, no. 3 (January 20, 2023): 553. http://dx.doi.org/10.3390/math11030553.

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The Kumaraswamy distribution is a common type of bounded distribution, which is widely used in agriculture, hydrology, and other fields. In this paper, we use the methods of the likelihood ratio test, modified information criterion, and Schwarz information criterion to analyze the change point of the Kumaraswamy distribution. Simulation experiments give the performance of the three methods. The application section illustrates the feasibility of the proposed method by applying it to a real dataset.

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19

Ma, Hongwei, Gan Yi, Jianmin Qi, and Zhenjie Zhang. "A Method for Solving Reliability of Route Travel Time." Journal of Function Spaces 2020 (April 27, 2020): 1–5. http://dx.doi.org/10.1155/2020/7867698.

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In order to obtain an effective method for solving route travel time reliability, this paper proposes an effective new method to calculate travel time reliability using an independent link travel time function. Based on several months of historical data, the results show that the Edgeworth expansion can better reflect travel time distribution law. In addition, travel time reliability can be calculated more conveniently by combining an approximate discretization algorithm and an empirical distribution function.

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20

Luo, Suichu, and David C. Joy. "A new method for quantitative analysis of EELS." Proceedings, annual meeting, Electron Microscopy Society of America 52 (1994): 950–51. http://dx.doi.org/10.1017/s0424820100172486.

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Techniques to remove plural scattering from electron energy loss spectra (EELS) are important in bot hmicroanalysis and other quantitative applications of electron spectroscopy. The techniques used are either based on convolution, or Fourier transform deconvolution, methods, in which either the elastic scattering angular correction or both elastic and inelastic angular corrections are not included. In this work we propose a new method based on both angular and energy loss three-dimension Poisson statistics which includes elastic and inelastic mixed angular scattering correction in order to obtain more accurate quantitative analysis for EELS.The electron scattering distribution determined by angular and energy loss three-dimension Poissonstatistics is given by:where IT is the total incident electron intensity; t is the sample thickness; λi, λe and λT are inelastic , elastic and total scattering mean free paths; Si (θ) and Se(θ) are normalized single inelastic and elastic angular scattering distributions respectively, F(E) is the single scattering normalized energy loss distribution.

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21

Cui, Hong Jun, Xiao Gao Xing, Guo Feng Liang, and Ya Ping Li. "Prediction Method for Freeway Wheelpath Distribution." Applied Mechanics and Materials 409-410 (September 2013): 1347–52. http://dx.doi.org/10.4028/www.scientific.net/amm.409-410.1347.

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According to the analysis of distributing characteristics which obtained by the investigation of different types vehicles of many freeways, the law is discovered that distributing characteristics of same types of vehicles are similar on different freeways, using test to certificate that distributions of same types of vehicles are submitted to identical normal distribution, and the rationality of this phenomenon is discussed with statistical point of view. Calculated and predicted method of wheelpath distribution and axle load distribution are established that based on traffic flow. In the end, an example is used to confirm the accuracy of this method by contrasting the survey result and the predicted result.

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22

Kong, Xiang Yu, Qun Yan, and Wen Sun. "Reliability Analysis Method for Distribution System with Distributed Generation." Applied Mechanics and Materials 448-453 (October 2013): 2649–53. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.2649.

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Distribution system reliability calculation models and assessment methods would change while connected with distributed generation. A reliability analysis method for distribution system with distributed generations was proposed in the paper, which makes an improvement of traditional distribution network minimum cut set method, and the characteristics of distributed generation and distribution network element reliability models are considered. Functional role of distributed generation in the power distribution system failure and distributed power adapter with load strategies were also analyzed in this method. Case simulation analysis was used to verify its effectiveness.

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23

Bora, Dhruba Jyoti, and Munindra Borah. "Regional analysis of maximum rainfall using L-moment and TL-moment: a comparative case study for the north East India." Journal of Applied and Natural Science 9, no. 4 (December 1, 2017): 2366–71. http://dx.doi.org/10.31018/jans.v9i4.1539.

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In this study it has been tried to develop a suitable model for maximum rainfall frequency analysis of the North East India using best fit probability distribution. The methods of L-moment have been employed for estimation of five probability distributions, namely Generalized extreme value (GEV), Generalized Logistic (GLO), Pearson type 3 (PE3), 3 parameter Log normal (LN3) and Generalized Pareto (GPA) distributions. The methods TL-moment have been used for estimating the parameters of three probability distributions namely Generalized extreme value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA) distributions. PE3 distribution has been selected as the best fit distribution using L-moment and GPA distribution using TL-moment method. Relative root mean square error (RRMSE) and Relative Bias (RBIAS) are employed to compare between the results found from L-moment and TL-moment analysis. It is found that PE3 distribution designated by L-moment method is the most suitable and the best fit distribution for rainfall frequency analysis of the North East India. Also the L-moment method is significantly more efficient than TL-moment.

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24

Ohtaka, Toshiya, and Shinichi Iwamoto. "A Grouping Method of Distribution Substations Using Cluster Analysis." IEEJ Transactions on Power and Energy 125, no. 3 (2005): 278–85. http://dx.doi.org/10.1541/ieejpes.125.278.

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25

Sudoh, Katsuzo, Yasuyuki Tanaka, Susumu Matsumoto, and Yasuyoshi Tozaki. "Load Distribution Analysis Method for Cylindrical Worm Gear Teeth." JSME international journal. Ser. C, Dynamics, control, robotics, design and manufacturing 39, no. 3 (1996): 606–13. http://dx.doi.org/10.1299/jsmec1993.39.606.

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26

Morris, P. R., R. E. Hook, and G. W. Whelan. "A New Composite-Sample Method for Orientation-Distribution Analysis." Textures and Microstructures 19, no. 1-2 (January 1, 1992): 1–8. http://dx.doi.org/10.1155/tsm.19.1.

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A new composite-sample method is suggested for crystallite orientation distribution analysis. The proposed method entails preparation of composites such that the surface to be examined is perpendicular to the rolling direction. The suggested reference frame is (—ND, TD, RD) for Roe's method. This choice simplifies expression of the results with respect to the conventional (RD, TD, ND) frame. A novel technique employing laser welding on three surfaces is used to bond adjacent sheet layers. The proposed composite-sample can be more easily and accurately constructed. It requires only about 12 percent of the material needed for Lopata and Kula's method. Existing programs for incomplete pole-figures have been modified to permit application of the new method. The method is expected to be statistically advantageous where materials develop “pancake”- or acicular-shaped grains. The method is illustrated for a deep-drawing aluminum-killed sheet steel, and results are compared with those obtained with a conventional sheet-sample.

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27

暴, 丽霞. "Analysis Method of Pore Size Distribution of Porous Materials." Material Sciences 10, no. 02 (2020): 95–103. http://dx.doi.org/10.12677/ms.2020.102012.

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28

KOMURA, Saburo, and Tsuyoshi NAKATANI. "A Digital Image Analysis Method for Velocity Distribution Measurements." PROCEEDINGS OF HYDRAULIC ENGINEERING 34 (1990): 671–76. http://dx.doi.org/10.2208/prohe.34.671.

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29

Xue, Huiwen, Haochen Li, and Yanfei Wang. "An Improved K-means Method with Density Distribution Analysis." MATEC Web of Conferences 176 (2018): 01019. http://dx.doi.org/10.1051/matecconf/201817601019.

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In this paper, a novel K-means clustering algorithm is proposed. Before running the traditional Kmeans, the cluster centers should be randomly selected, which would influence the time cost and accuracy. To solve this problem, we utilize density distribution analysis in the traditional K-means. For a reasonable cluster, it should have a dense inside structure which means the points in the same cluster should tightly surround the center, while separated away from other cluster canters. Based on this assumption, two quantities are firstly introduced: the local density of cluster center ρi and its desperation degree δi, then some reasonable cluster centers candidates are selected from the original data. We performed our algorithm on three synthetic data and a real bank business data to evaluate its accuracy and efficiency. Comparing with Traditional K-means and K-means++, the results demonstrated that the improved method performs better.

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30

Teng, Jen-Hao, Shu-Hung Liao, and Rong-Ceng Leou. "Three-Phase Harmonic Analysis Method for Unbalanced Distribution Systems." Energies 7, no. 1 (January 20, 2014): 365–84. http://dx.doi.org/10.3390/en7010365.

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31

Gurram, Ravindranath, and B. Subramanyam. "Sensitivity analysis of radial distribution network – adjoint network method." International Journal of Electrical Power & Energy Systems 21, no. 5 (June 1999): 323–26. http://dx.doi.org/10.1016/s0142-0615(98)00058-1.

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32

Leung, A. Y. T., A. K. H. Kwan, and W. E. Zhou. "Static-dynamic distribution factors method for tall building analysis." Computers & Structures 46, no. 3 (February 1993): 495–503. http://dx.doi.org/10.1016/0045-7949(93)90219-4.

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33

Basha, H. A., and B. G. Kassab. "Analysis of water distribution systems using a perturbation method." Applied Mathematical Modelling 20, no. 4 (April 1996): 290–97. http://dx.doi.org/10.1016/0307-904x(95)00122-z.

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34

Das, S. "Distribution selection for hydrologic frequency analysis using subsampling method." IOP Conference Series: Earth and Environmental Science 39 (August 2016): 012059. http://dx.doi.org/10.1088/1755-1315/39/1/012059.

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35

Teng, Jen-Hao. "Systematic short-circuit-analysis method for unbalanced distribution systems." IEE Proceedings - Generation, Transmission and Distribution 152, no. 4 (2005): 549. http://dx.doi.org/10.1049/ip-gtd:20045132.

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36

Abareshi, Maryam, Seyed Mahmood Hosseini, and Ahmad Aftabi Sani. "A simple iterative method for water distribution network analysis." Applied Mathematical Modelling 52 (December 2017): 274–87. http://dx.doi.org/10.1016/j.apm.2017.07.053.

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37

R�vay, Zsolt. "Analysis of the probability distribution method for spectrum decomposition." Mikrochimica Acta 126, no. 1-2 (March 1997): 77–81. http://dx.doi.org/10.1007/bf01242665.

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38

Septiyana, Angga, Ardian Rizaldi, Kurnia Hidayat, and Yusuf Giri Wijaya. "COMPARATIVE STUDY OF WING LIFT DISTRIBUTION ANALYSIS USING NUMERICAL METHOD." Jurnal Teknologi Dirgantara 18, no. 2 (December 27, 2020): 129. http://dx.doi.org/10.30536/j.jtd.2020.v18.a3349.

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This research focuses on calculating the force distribution on the wings of the LSU 05-NG aircraft by several numerical methods. Analysis of the force distribution on the wing is important because the wing has a very important role in producing sufficient lift for the aircraft. The numerical methods used to calculate the lift force distribution on the wings are Computational Flow Dynamics (CFD), Lifting Line Theory, Vortex Lattice Method and 3D Panel Method. The numerical methods used will be compared with each other to determine the accuracy and time required to calculate wing lift distribution. Because CFDs produce more accurate estimates, CFD is used as the main comparison for the other three numerical methods. Based on calculations performed, 3D Panel Method has an accuracy that is close to CFD with a shorter time. 3D Panel Method requires 400 while CFD 1210 seconds with results that are not much different. While LLT and VLM have poor accuracy, however, shorter time is needed. Therefore to analyze the distribution of lift force on the wing it is enough to use the 3D Panel Method due to accurate results and shorter computing time.

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Mikhailov, Gennady A., Natalya V. Tracheva, and Sergey A. Ukhinov. "A new kernel-projective statistical estimator in the Monte Carlo method." Russian Journal of Numerical Analysis and Mathematical Modelling 35, no. 6 (December 16, 2020): 341–53. http://dx.doi.org/10.1515/rnam-2020-0028.

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AbstractIn the present paper, we propose a new combined kernel-projective statistical estimator of the two-dimensional distribution density, where the first ‘main’ variable is processed with the kernel estimator, and the second one is processed with the projective estimator for the conditional distribution density. In this case, statistically estimated coefficients of some orthogonal expansion of the conditional distribution density are used for each ‘kernel’ interval defined by a micro-sample. The root-mean-square optimization of such an estimator is performed under the assumptions concerning the convergence rate of the used orthogonal expansion. The numerical study of the constructed estimator is implemented for angular distributions of the radiation flux forward-scattered and backscattered by a layer of matter. A comparative analysis of the results is performed for molecular and aerosol scattering.

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40

Zenkov, Andrei, Eugene Zenkov, and Ansgar Belke. "A Novel Text Analysis Method: Numerals Reveal the Author." SHS Web of Conferences 93 (2021): 03026. http://dx.doi.org/10.1051/shsconf/20219303026.

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Two approaches to the statistical analysis of texts are suggested, both based on the study of numerals occurring in literary texts. The first approach is related to the study of the frequency distribution of various leading digits of numerals occurring in the text. This approach is convenient for testing whether a group of texts has common authorship: the latter is dubious if the frequency distributions are sufficiently different. The second approach requires the study of the frequencies of numerals themselves. The approach yields information about the author, stylistic and genre peculiarities of the texts and is suited for advanced study of authorial texts. The hypothesis that I. Ilf and E. Petrov are fake authors of novels "The Twelve Chairs" and "The Little Golden Calf", and they were ghosted by M. Bulgakov, is checked. The frequency distribution of numerals, as well as its cluster analysis, do not confirm this hypothesis.

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41

Reed, George F., Bruce D. Meade, and Mark C. Steinhoff. "The Reverse Cumulative Distribution Plot: A Graphic Method for Exploratory Analysis of Antibody Data." Pediatrics 96, no. 3 (September 1, 1995): 600–603. http://dx.doi.org/10.1542/peds.96.3.600.

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Serologic data often have a wide range and commonly do not approximate a normal distribution. Means, medians, SDs, or other conventional numerical summaries of antibody data may not adequately or fully describe these complex data. The reverse cumulative distribution plot is a graphic tool that completely displays all the data, allows a rapid visual assessment of important details of the distribution, and simplifies comparison of distributions.

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42

Teng, Fei, Yun Lin, Yanping Wang, Wenjie Shen, Shanshan Feng, and Wen Hong. "An Anisotropic Scattering Analysis Method Based on the Statistical Properties of Multi-Angular SAR Images." Remote Sensing 12, no. 13 (July 5, 2020): 2152. http://dx.doi.org/10.3390/rs12132152.

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The scatterings of many targets are aspect dependent, which is called anisotropy. Multi-angular synthetic aperture radar (SAR) is a suitable means of detecting this kind of anisotropic scattering behavior by viewing targets from different aspect angles. First, the statistical properties of anisotropic and isotropic scatterings are studied in this paper. X-band chamber circular SAR data are used. The result shows that isotropic scatterings have stable distributions in different aspect viewing angles while the distributions of anisotropic scatterings are various. Then the statistical properties of single polarization high-resolution multi-angular SAR images are modeled by different distributions. G 0 distribution performs best in all types of areas. An anisotropic scattering analysis method based on the multi-angular statistical properties is proposed. A likelihood ratio test based on G 0 distribution is used to measure the anisotropy. Anisotropic scatterings can be discriminated from isotropic scatterings by thresholding. Besides, the scattering direction can also be estimated by our method. AHH polarization C-band circular SAR data are used to validate our method. The result of using G 0 distribution is compared with the result of using Rayleigh distribution. The result of using G 0 distribution is the better one.

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43

Liu, Yan, Wenxue Li, and Jiqiang Feng. "Graph-Theoretical Method to the Existence of Stationary Distribution of Stochastic Coupled Systems." Journal of Dynamics and Differential Equations 30, no. 2 (November 21, 2016): 667–85. http://dx.doi.org/10.1007/s10884-016-9566-y.

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44

Eddy, David M., Vic Hasselblad, and Ross Shachter. "A Bayesian Method for Synthesizing Evidence: The Confidence Profile Method." International Journal of Technology Assessment in Health Care 6, no. 1 (January 1990): 31–55. http://dx.doi.org/10.1017/s0266462300008928.

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This article describes a collection of meta-analysis techniques based on Bayesian statistics for interpreting, adjusting, and combining evidence to estimate parameters and outcomes important to the assessment of health technologies. The result of an analysis by the Confidence Profile Method is a joint posterior probability distribution for the parameters of interest, from which marginal distributions for any particular parameter can be calculated. The method can be used to analyze problems involving a variety of types of outcomes, a variety of measures of effect, and a variety of experimental designs. This article presents the elements necessary for analysis, including prior distributions, likelihood functions, and specific models for experimental designs that include adjustment for biases.

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SASAKI, TAKESHI, IKUO HAGIWARA, KASTUJI SASAKI, RYUNOSHIN YOSHINAKA, YUZO OHNISHI, SATISHI NISHIYAMA, and TOMOFUMI KOYAMA. "STABILITY ANALYSES FOR ANCIENT MASONRY STRUCTURES USING DISCONTINUOUS DEFORMATION ANALYSIS AND NUMERICAL MANIFOLD METHOD." International Journal of Computational Methods 08, no. 02 (June 2011): 247–75. http://dx.doi.org/10.1142/s0219876211002575.

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In this paper, the stability including stress distribution of two ancient masonry structures, the pyramid of the Pharaoh Khufu, Egypt and the Pont of Gard, were analyzed using discontinuous deformation analysis (DDA) and numerical manifold method (NMM). For the simulation using NMM, the newly developed four-node isoparametric element was used. The stress distributions/concentration were calculated and compared between the two methods. The calculated results show qualitative agreement with observations. DDA and NMM are applicable to simulate the physical phenomena of masonry structures.

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Hao, Guang Bo, and Li Yang Xie. "Damage Equivalent Method of Fatigue Reliability Analysis of Load-Sharing Parallel System." Advanced Materials Research 44-46 (June 2008): 853–58. http://dx.doi.org/10.4028/www.scientific.net/amr.44-46.853.

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As for load-sharing parallel system like multi-engine system and wire cable, dependence-failure must occur due to load redistributing, so the component life distributions changed. After the analysis of the disadvantage of failure probability equivalent principle and the transformation of equivalent working time of different life distribution based on damage equivalent principle, the parallel system reliability model applying full probability formula is established. The established reliability model provides a new method for reliability analysis of load-sharing parallel system whose component life follows any distribution.

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Lodder, Robert A., and Gary M. Hieftje. "Quantile Analysis: A Method for Characterizing Data Distributions." Applied Spectroscopy 42, no. 8 (November 1988): 1512–20. http://dx.doi.org/10.1366/0003702884429724.

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Analyzing distributions of data represents a common problem in chemistry. Quantile-quantile (QQ) plots provide a useful way to attack this problem. These graphs are often used in the form of the normal probability plot, to determine whether the residuals from a fitting process are randomly distributed and therefore whether an assumed model fits the data at hand. By comparing the integrals of two probability density functions in a single plot, QQ plotting methods are able to capture the location, scale, and skew of a data set. This procedure provides more information to the analyst than do classical statistical methods that rely on a single test statistic for distribution comparisons.

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Zheng, Yi, and Ling Wang. "Time-Space Characteristics Distribution of Traffic Accidents Based on Clustering Analysis." Advanced Materials Research 684 (April 2013): 604–7. http://dx.doi.org/10.4028/www.scientific.net/amr.684.604.

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This paper uses clustering analysis method to explore time-space characteristics distribution of traffic accidents, losses converted into cash, number of deaths and injuries. We select hierarchical clustering method to analyze about 458 thousands road traffic accidents in china from 2009 to 2010. And the time-space characteristics distributions include month distribution, annual average daily distribution, annual average daily time of occurrence distribution, road type distribution, road alignment distribution. The results show that traffic accidents on expressway are bound up with these characteristics.

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Baharith, Lamya A., and Wedad H. Aljuhani. "New Method for Generating New Families of Distributions." Symmetry 13, no. 4 (April 20, 2021): 726. http://dx.doi.org/10.3390/sym13040726.

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This article presents a new method for generating distributions. This method combines two techniques—the transformed—transformer and alpha power transformation approaches—allowing for tremendous flexibility in the resulting distributions. The new approach is applied to introduce the alpha power Weibull—exponential distribution. The density of this distribution can take asymmetric and near-symmetric shapes. Various asymmetric shapes, such as decreasing, increasing, L-shaped, near-symmetrical, and right-skewed shapes, are observed for the related failure rate function, making it more tractable for many modeling applications. Some significant mathematical features of the suggested distribution are determined. Estimates of the unknown parameters of the proposed distribution are obtained using the maximum likelihood method. Furthermore, some numerical studies were carried out, in order to evaluate the estimation performance. Three practical datasets are considered to analyze the usefulness and flexibility of the introduced distribution. The proposed alpha power Weibull–exponential distribution can outperform other well-known distributions, showing its great adaptability in the context of real data analysis.

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Suzer, Ahmet Esat, and Aziz Kaba. "A probabilistic-based analysis for wind distribution determination of a runway." Aircraft Engineering and Aerospace Technology 93, no. 2 (February 12, 2021): 284–97. http://dx.doi.org/10.1108/aeat-09-2020-0207.

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Purpose The purpose of this study is to describe precisely the wind speed regime and characteristics of a runway of an International Airport, the north-western part of Turkey. Design methodology approach Three different probability distributions, namely, Inverse Gaussian (IG), widely used two-parameter Weibull and Rayleigh distributions in the literature, are used to represent wind regime and characteristics of the runway. The parameters of each distribution are estimated by the pattern search (PS)-based heuristic algorithm. The results are compared with the other three methods-based numerical computation, including maximum-likelihood method, moment method (MoM) and power density method, respectively. To evaluate the fitting performance of the proposed method, several statistical goodness tests including the mostly used root mean square error (RMSE) and chi-squared (X2) are conducted. Findings In the light of the statistical goodness tests, the results of the IG-based PS attain better performance than the classical Weibull and Rayleigh functions. Both the RMSE and X2 values achieved by the IG-based PS method lower than that of Weibull and Rayleigh distributions. It exhibits a better fitting performance with 0.0074 for RMSE and 0.58 × 10−4 for X2 for probability density function (PDF) in 2012 and with RMSE of 0.0084 and X2 of 0.74 × 10−4 for PDF in 2013. As regard the cumulative density function of the measured wind data, the best results are found to be Weibull-based PS with RMSE of 0.0175 and X2 of 3.25 × 10−4 in 2012. However, Weibull-based MoM shows more excellent ability in 2013, with RMSE of 0.0166 and X2 of 2.94 × 10−4. Consequently, it is considered that the results of this study confirm that IG-based PS with the lowest error value can a good choice to model more accurately and characterize the wind speed profile of the airport. Practical implications This paper presents a realistic point of view regarding the wind regime and characteristics of an airport. This study may cast the light on researchers, policymakers, policy analysts and airport designers intending to investigate the wind profile of a runway at the airport in the world and also provide a significant pathway on how to determine the wind distribution of the runway. Originality value Instead of the well-known Weibull distribution for the representing of wind distribution in the literature, in this paper, IG distribution is used. Furthermore, the suitability of IG to represent the wind distribution is validated when compared with two-parameter Weibull and Rayleigh distributions. Besides, the performance and efficiency of PS have been evaluated by comparing it with other methods.

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