Статті в журналах: "Probabilistic-statistical method"

1

Bidyuk, Petro I., and Nataliia V. Kuznietsova. "Probabilistic-Statistical Method for Risk Assessment of Financial Losses." Research Bulletin of the National Technical University of Ukraine "Kyiv Politechnic Institute", no. 2 (June 12, 2018): 7–17. http://dx.doi.org/10.20535/1810-0546.2018.2.128989.

Повний текст джерела

Стилі APA, Harvard, Vancouver, ISO та ін.

2

Holmes, C. C., and N. M. Adams. "A probabilistic nearest neighbour method for statistical pattern recognition." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 64, no. 2 (May 2002): 295–306. http://dx.doi.org/10.1111/1467-9868.00338.

Повний текст джерела

Стилі APA, Harvard, Vancouver, ISO та ін.

3

Liu, Yan. "Analysis and Research on the Application of Sampling Big Data Statistical Method." BCP Business & Management 13 (November 16, 2021): 164–69. http://dx.doi.org/10.54691/bcpbm.v13i.86.

Повний текст джерела

Анотація:

Under the current statistical environment and technical conditions, there is a certain lag in the publication of statistical data. This means that there is a time lag in the completion of reports, which may delay the judgment of the current economic situation. Network real-time analysis based on big data analysis has gradually become the main force of data analysis. This paper puts forward the basic idea of understanding the statistical inference problem of non-probabilistic sampling. Sampling methods can consider sample selection based on sample matching, link tracking sampling method, etc., so that the obtained non-probabilistic samples are like probabilistic samples, so the statistical inference theory of probabilistic samples can be adopted. Random sampling technology and non-random sampling technology still have many applicable scenes, which are not only the scenes of traditional sampling survey in the past, but also applied to more modern information scenes with the times.

Стилі APA, Harvard, Vancouver, ISO та ін.

4

Pelizzola, Alessandro. "Cluster variation method in statistical physics and probabilistic graphical models." Journal of Physics A: Mathematical and General 38, no. 33 (August 3, 2005): R309—R339. http://dx.doi.org/10.1088/0305-4470/38/33/r01.

Повний текст джерела

Стилі APA, Harvard, Vancouver, ISO та ін.

5

Smugala, S., and D. Kubečková. "Construction Process Duration Predicted by Statistical Method." IOP Conference Series: Materials Science and Engineering 1203, no. 3 (November 1, 2021): 032135. http://dx.doi.org/10.1088/1757-899x/1203/3/032135.

Повний текст джерела

Анотація:

Abstract Many construction projects today are planned and managed using computer technology. An integral part of the management of these projects is sophisticated software, which includes statistical probabilistic methods. The main task in this area is direct verification of the validity of planned labour productivity values during the construction process according to the recorded average performance values. Using selected statistical methods and analyses, a case study can document this type of undertaking, for example, in a selected masonry process in which the upper and lower limits of performance, i.e. the optimistic and pessimistic bounds, may be calculated with 95% probability. Evaluation of these performance parameters in the construction software used for this study showed a difference in time of 11 days at the end of the process. The figures indicated a 9.6% and 14.3% decrease in labour productivity, respectively, for the optimistic and pessimistic values compared to the construction software ’ s planned values. Repeated evaluation of performance can aid in improving labour productivity and attaining project milestones and subsequent construction deadlines during the construction process. This paper aims to confirm or refute this theoretical balance using probabilistic statistical methods and to emphasize the importance of statistical analysis in the real construction process with the use of the software.

Стилі APA, Harvard, Vancouver, ISO та ін.

6

HIROHATA, Kenji, Katsumi HISANO, Hiroyuki TAKAHASHI, Minoru MUKAI, Noriyasu KAWAMURA, Hideo IWASAKI, Takashi KAWAKAMI, Qiang YU, and Masaki SHIRATORI. "Proposal of the Method for Multidisciplinary Reliability Analysis Based on Statistical and Probabilistic Methods." Transactions of the Japan Society of Mechanical Engineers Series A 71, no. 705 (2005): 740–48. http://dx.doi.org/10.1299/kikaia.71.740.

Повний текст джерела

Стилі APA, Harvard, Vancouver, ISO та ін.

7

Kurguzov, Konstantin V., Igor K. Fomenko, and Daria D. Shubina. "Probabilistic and statistical modeling of loads and forces." Vestnik MGSU, no. 9 (September 2020): 1249–61. http://dx.doi.org/10.22227/1997-0935.2020.9.1249-1261.

Повний текст джерела

Анотація:

Introduction. At present, numerical methods enjoy widespread use in construction practice. They enable performing and analyzing complex non-linear, multi-factor models without excessive analytical procedures. However, as a rule, the most complex tasks, performed in a three-dimensional setting with account taken of physical, geometric and other nonlinearities, are performed in deterministic formulations without the analysis of the stochastic nature of physical processes. This seems particularly strange, given that numerical methods are well-suited for modeling stochastic processes. Numerical probabilistic and statistical approaches (PSA) can be applied to simulate and take into consideration various spatiotemporal aspects of the probabilistic nature of loads and forces, structural system resistances, materials and geological terrains. Even the most advanced numerical models of deterministic physical systems are merely a specific case of probabilistic and statistical modeling: they enable obtaining only one value (point) on the whole field of possible implementations, being unable to demonstrate an objective and exhaustive variety of probable outcomes. This article presents a case study of numerical probabilistic and statistical analyses of loads and forces. Methods of research. Materials from different sources, such as reference books, regulatory documents, laboratory test results, as well as available experimental data, were used as input parameters. The principal calculation and analysis of the integral function of loads was performed using the Monte Carlo numerical method of probabilistic and statistical modeling and various theoretical (statistical) and empirical distributions, followed by the quantitative assessment of design loads at various confidence probability values. Results. This study provides an example of the probabilistic and statistical calculation (determination) of the integral function of loads and forces with account taken of different origins of loads and varied input parameter distribution patterns, including empirical distributions. It has proven great importance of accurate description of initial distributions of a random value for the determination of reliable design load values. Conclusions. Probabilistic and statistical approaches have the ability to objectively assess the performance of structural systems based on the quantitative assessment of the probabilistic nature of load factors. These approaches have huge potential for increasing the reliability of buildings and structures and the cost effectiveness of construction projects.

Стилі APA, Harvard, Vancouver, ISO та ін.

8

Wu, Yongxin, Yufeng Gao, Limin Zhang, and Jun Yang. "How distribution characteristics of a soil property affect probabilistic foundation settlement — from the aspect of the first four statistical moments." Canadian Geotechnical Journal 57, no. 4 (April 2020): 595–607. http://dx.doi.org/10.1139/cgj-2019-0089.

Повний текст джерела

Анотація:

The effects of the first four statistical moments defining the statistical characteristic of elastic modulus on the probabilistic foundation settlement are investigated in this study. By combining the Hermite probability model and spectral representation method, a method to simulate nonGaussian homogenous fields based on the first four statistical moments is proposed. Linear elastic finite element models are employed to study the total settlement and the differential settlement of a shallow foundation. Probabilistic measurements of total–differential settlement obtained by the Monte Carlo simulations are presented. For the cases considered, the effects of skewness and kurtosis defining the probabilistic characteristic of elastic modulus on the total–differential settlement of a probabilistic foundation are illustrated. The computed results show that the value of skewness has a more significant effect on the probabilistic foundation settlement than kurtosis, and the case with the smallest skewness is observed as the most critical one.

Стилі APA, Harvard, Vancouver, ISO та ін.

9

Užpolevičius, Benediktas. "PROBABILISTIC AND STATISTICAL METHODS FOR DESIGNING AND ANALYZING LIMIT STATES/TIKIMYBINIS IR STATISTINIS RIBINŲ BŪVIŲ PROJEKTAVIMO IR ANALIZĖS METODAI." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 7, no. 5 (October 31, 2001): 413–18. http://dx.doi.org/10.3846/13921525.2001.10531763.

Повний текст джерела

Анотація:

Errors of partial reliability factor (PRF) method, being used in operating codes to provide required reliability of construction work (foundations, structures and their systems), are discussed. It is pointed out that additional resistance (strength, stiffness, etc) of the members to compensate these errors is required, and it makes much more than 10%. The main cause of these shortcomings is that in the PRF method, for the sake of simplicity, independent partial coefficients and limited number of these coefficients are applied. Direct probabilistic and statistical methods (without application of partial coefficients and design values) are proposed. It is demonstrated that these methods are free of systematic errors which are characteristic of the known codified (standardized) probability calculations. The proposed methods make up a unified method used for foundations and structures, uniformly based on theoretical conclusions of probability theory and mathematical statistics. These economy seeking methods are intended for effective use (without change of codes) of available additional information, which is made of different amount of data of statistical measurements or statistical observations on minimal values of soils and building material mechanical characteristics of structures and maximum values of loads, actions and their combinations during the operation period, geometrical dimensions of critical cross-sections, errors of algorithms for calculation of resistance and action effects, control errors made by people during design, construction, operation of construction works, etc. In case of a limited amount of information the proposed statistical model is to be used. In addition, the proposed method is adjusted for effective use of the known reliability solutions of economical and social optimisation (in relation to economical and social damage caused by the limit state, human safety and other factors) co-ordinating them with application experience of PRF code method and statistical multidimensional data of limit state frequency. Areas of application and economy of the proposed probabilistic and statistical methods are presented in Table 1. National and established specifications prepared for probabilistic and statistical calculation design and tests of foundations, structures and their systems are discussed. Practical application and economical comparison of calculation of construction members by PRF, probabilistic and statistical methods (area of the cross-section, foundation pad base A % in relation to that determined by SNiP codes)

Стилі APA, Harvard, Vancouver, ISO та ін.

10

Karakus, S., and K. Demırcı. "Statistical Convergence of Double Sequences on Probabilistic Normed Spaces." International Journal of Mathematics and Mathematical Sciences 2007 (2007): 1–11. http://dx.doi.org/10.1155/2007/14737.

Повний текст джерела

Анотація:

The concept of statistical convergence was presented by Steinhaus in 1951. This concept was extended to the double sequences by Mursaleen and Edely in 2003. Karakus has recently introduced the concept of statistical convergence of ordinary (single) sequence on probabilistic normed spaces. In this paper, we define statistical analogues of convergence and Cauchy for double sequences on probabilistic normed spaces. Then we display an exampl e such that our method of convergence is stronger than usual convergence on probabilistic normed spaces. Also we give a useful characterization for statistically convergent double sequences.

Стилі APA, Harvard, Vancouver, ISO та ін.

11

Zhou, Changcong, Chenghu Tang, Fuchao Liu, and Wenxuan Wang. "A Probabilistic Representation Method for Interval Uncertainty." International Journal of Computational Methods 15, no. 05 (June 5, 2018): 1850038. http://dx.doi.org/10.1142/s021987621850038x.

Повний текст джерела

Анотація:

In this work, we consider the interval uncertainty from the probabilistic point of view, focusing on the establishment of probabilistic representation of interval uncertainty. A model-free sampling technique is first introduced, which can be used to produce a considerably larger sample from a given small sample. To make sure the local statistical characteristics of these two samples coincide, an improved model-free sampling technique is introduced based on probability weighted moments. The improved model-free sampling technique is then applied to obtain a large sample based on interval data, of which the probability distribution is produced by the kernel density estimator. Highest density regions based on estimated probability density function have been considered to further investigate the underlying information. The proposed probabilistic representation method is employed in the attempt of interval uncertainty propagation with the results compared with previous studies. The research adds a possible tool in the treatment of interval uncertainty.

Стилі APA, Harvard, Vancouver, ISO та ін.

12

Hagihara, Yukito, Chikahito Ito, Daizen Kirikae, Noriyuki Hisamori, Hiroshi Suzuki, and Kenichi Takai. "Probabilistic and Statistical Evaluation of Delayed Fracture Characteristics Obtained by CSRT Method." Tetsu-to-Hagane 95, no. 6 (2009): 489–97. http://dx.doi.org/10.2355/tetsutohagane.95.489.

Повний текст джерела

Стилі APA, Harvard, Vancouver, ISO та ін.

13

Yucel, Abdulkadir C., Hakan Bagci, and Eric Michielssen. "An Adaptive Multi-Element Probabilistic Collocation Method for Statistical EMC/EMI Characterization." IEEE Transactions on Electromagnetic Compatibility 55, no. 6 (December 2013): 1154–68. http://dx.doi.org/10.1109/temc.2013.2265047.

Повний текст джерела

Стилі APA, Harvard, Vancouver, ISO та ін.

14

Thorndahl, S., K. Schaarup-Jensen, and J. B. Jensen. "Probabilistic modelling of combined sewer overflow using the First Order Reliability Method." Water Science and Technology 57, no. 9 (May 1, 2008): 1337–44. http://dx.doi.org/10.2166/wst.2008.301.

Повний текст джерела

Анотація:

This paper presents a new and alternative method (in the context of urban drainage) for probabilistic hydrodynamical analysis of drainage systems in general and especially prediction of combined sewer overflow. Using a probabilistic shell it is possible to implement both input and parameter uncertainties on an application of the commercial urban drainage model MOUSE combined with the probabilistic First Order Reliability Method (FORM). Applying statistical characteristics on several years of rainfall, it is possible to derive a parameterization of the rainfall input and the failure probability and return period of combined sewer overflow to receiving waters can be found.

Стилі APA, Harvard, Vancouver, ISO та ін.

15

Hall, Richard J., Adam A. Scaife, Edward Hanna, Julie M. Jones, and Robert Erdélyi. "Simple Statistical Probabilistic Forecasts of the Winter NAO." Weather and Forecasting 32, no. 4 (August 1, 2017): 1585–601. http://dx.doi.org/10.1175/waf-d-16-0124.1.

Повний текст джерела

Анотація:

Abstract The variability of the North Atlantic Oscillation (NAO) is a key aspect of Northern Hemisphere atmospheric circulation and has a profound impact upon the weather of the surrounding landmasses. Recent success with dynamical forecasts predicting the winter NAO at lead times of a few months has the potential to deliver great socioeconomic impacts. Here, a linear regression model is found to provide skillful predictions of the winter NAO based on a limited number of statistical predictors. Identified predictors include El Niño, Arctic sea ice, Atlantic SSTs, and tropical rainfall. These statistical models can show significant skill when used to make out-of-sample forecasts, and the method is extended to produce probabilistic predictions of the winter NAO. The statistical hindcasts can achieve similar levels of skill to state-of-the-art dynamical forecast models, although out-of-sample predictions are less skillful, albeit over a small period. Forecasts over a longer out-of-sample period suggest there is true skill in the statistical models, comparable with that of dynamical forecasting models. They can be used both to help evaluate and to offer insight into the sources of predictability and limitations of dynamical models.

Стилі APA, Harvard, Vancouver, ISO та ін.

16

Peng, Xiang, Qilong Gao, Jiquan Li, Zhenyu Liu, Bing Yi, and Shaofei Jiang. "Probabilistic Representation Approach for Multiple Types of Epistemic Uncertainties Based on Cubic Normal Transformation." Applied Sciences 10, no. 14 (July 8, 2020): 4698. http://dx.doi.org/10.3390/app10144698.

Повний текст джерела

Анотація:

Many non-probabilistic approaches have been widely regarded as mathematical tools for the representation of epistemic uncertainties. However, their heavy computational burden and low computational efficiency hinder their applications in practical engineering problems. In this article, a unified probabilistic representation approach for multiple types of epistemic uncertainties is proposed based on the cubic normal transformation method. The epistemic uncertainties can be represented using an interval approach, triangular fuzzy approach, or evidence theory. The uncertain intervals of four statistical moments, which contain mean, variance, skewness, and kurtosis, are calculated using the sampling analysis method. Subsequently, the probabilistic cubic normal distribution functions are conducted for sampling points of four statistical moments of epistemic uncertainties. Finally, a calculation procedure for the construction of probabilistic representation functions is proposed, and these epistemic uncertainties are represented with belief and plausibility continuous probabilistic measure functions. Two numerical examples and one engineering example demonstrate that the proposed approach can act as an accurate probabilistic representation function with high computational efficiency.

Стилі APA, Harvard, Vancouver, ISO та ін.

17

Boychuk, M. I., L. A. Vasileva, and S. A. Mikaeva. "METHOD FOR CALCULATING THE RELIABILITY OF QUARTZ RESONATORS." Spravochnik. Inzhenernyi zhurnal, no. 280 (July 2020): 53–58. http://dx.doi.org/10.14489/hb.2020.07.pp.053-058.

Повний текст джерела

Анотація:

In the process of developing a thermocompensated quartz generator, it was necessary to calculate the reliability indicators of such an important element of the circuit as a quartz resonator for a failure-free period of 15 000 hours. The main parameter that can be used to evaluate the reliability of the quartz resonator is the stability of the nominal oscillation frequency. It is the stability of the nominal frequency of the resonator that formed the basis of the new developed technique. The method includes rules for constructing a probabilistic and statistical model of the dependence of the resonator frequency change on the test time. The article describes the work done on the accelerated evaluation of the reliability of piezoelectric resonators RK563 on the basis of probabilistic and statistical modeling of the behavior of the frequency from the test time. The method of mathematical modeling is based on the results of incomplete tests for a period of 30…50 % of the set value of the minimum operating time.

Стилі APA, Harvard, Vancouver, ISO та ін.

18

Boychuk, M. I., L. A. Vasileva, and S. A. Mikaeva. "METHOD FOR CALCULATING THE RELIABILITY OF QUARTZ RESONATORS." Spravochnik. Inzhenernyi zhurnal, no. 280 (July 2020): 53–58. http://dx.doi.org/10.14489/hb.2020.07.pp.053-058.

Повний текст джерела

Анотація:

In the process of developing a thermocompensated quartz generator, it was necessary to calculate the reliability indicators of such an important element of the circuit as a quartz resonator for a failure-free period of 15 000 hours. The main parameter that can be used to evaluate the reliability of the quartz resonator is the stability of the nominal oscillation frequency. It is the stability of the nominal frequency of the resonator that formed the basis of the new developed technique. The method includes rules for constructing a probabilistic and statistical model of the dependence of the resonator frequency change on the test time. The article describes the work done on the accelerated evaluation of the reliability of piezoelectric resonators RK563 on the basis of probabilistic and statistical modeling of the behavior of the frequency from the test time. The method of mathematical modeling is based on the results of incomplete tests for a period of 30…50 % of the set value of the minimum operating time.

Стилі APA, Harvard, Vancouver, ISO та ін.

19

Veldkamp, Simon, Kirien Whan, Sjoerd Dirksen, and Maurice Schmeits. "Statistical Postprocessing of Wind Speed Forecasts Using Convolutional Neural Networks." Monthly Weather Review 149, no. 4 (April 2021): 1141–52. http://dx.doi.org/10.1175/mwr-d-20-0219.1.

Повний текст джерела

Анотація:

AbstractCurrent statistical postprocessing methods for probabilistic weather forecasting are not capable of using full spatial patterns from the numerical weather prediction (NWP) model. In this paper, we incorporate spatial wind speed information by using convolutional neural networks (CNNs) and obtain probabilistic wind speed forecasts in the Netherlands for 48 h ahead, based on KNMI’s deterministic HARMONIE-AROME NWP model. The probabilistic forecasts from the CNNs are shown to have higher Brier skill scores for medium to higher wind speeds, as well as a better continuous ranked probability score (CRPS) and logarithmic score, than the forecasts from fully connected neural networks and quantile regression forests. As a secondary result, we have compared the CNNs using three different density estimation methods [quantized softmax (QS), kernel mixture networks, and fitting a truncated normal distribution], and found the probabilistic forecasts based on the QS method to be best.

Стилі APA, Harvard, Vancouver, ISO та ін.

20

Berrocal, Veronica J., Adrian E. Raftery, and Tilmann Gneiting. "Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts." Monthly Weather Review 135, no. 4 (April 1, 2007): 1386–402. http://dx.doi.org/10.1175/mwr3341.1.

Повний текст джерела

Анотація:

Abstract Forecast ensembles typically show a spread–skill relationship, but they are also often underdispersive, and therefore uncalibrated. Bayesian model averaging (BMA) is a statistical postprocessing method for forecast ensembles that generates calibrated probabilistic forecast products for weather quantities at individual sites. This paper introduces the spatial BMA technique, which combines BMA and the geostatistical output perturbation (GOP) method, and extends BMA to generate calibrated probabilistic forecasts of whole weather fields simultaneously, rather than just weather events at individual locations. At any site individually, spatial BMA reduces to the original BMA technique. The spatial BMA method provides statistical ensembles of weather field forecasts that take the spatial structure of observed fields into account and honor the flow-dependent information contained in the dynamical ensemble. The members of the spatial BMA ensemble are obtained by dressing the weather field forecasts from the dynamical ensemble with simulated spatially correlated error fields, in proportions that correspond to the BMA weights for the member models in the dynamical ensemble. Statistical ensembles of any size can be generated at minimal computational cost. The spatial BMA technique was applied to 48-h forecasts of surface temperature over the Pacific Northwest in 2004, using the University of Washington mesoscale ensemble. The spatial BMA ensemble generally outperformed the BMA and GOP ensembles and showed much better verification results than the raw ensemble, both at individual sites, for weather field forecasts, and for forecasts of composite quantities, such as average temperature in National Weather Service forecast zones and minimum temperature along the Interstate 90 Mountains to Sound Greenway.

Стилі APA, Harvard, Vancouver, ISO та ін.

21

Yan, Lei, and Ying Chen Liu. "Assessment Method of Stress Reliability Based on Effective Prestress Testing for Existing PC Bridge." Advanced Materials Research 368-373 (October 2011): 2452–56. http://dx.doi.org/10.4028/www.scientific.net/amr.368-373.2452.

Повний текст джерела

Анотація:

In order to investigate the emergency capacity of the full prestress and A-class components under normal service conditions, vertical tensioned increment method was be applied to study the statistic discipline of effective prestress for existing PC bridges. The results showed that the statistical parameters of effective prestress obey normal distribution and ~N(0.97,0.09). On this basis, the stress-resisting probabilistic models of two kinds of components were constructed. The dead load effect probabilistic model and the vehicle load probabilistic model considering evaluation base period were established. Based on the research above, the assessment method of stress reliability for PC bridge under normal service conditions was presented.

Стилі APA, Harvard, Vancouver, ISO та ін.

22

Jaakkola, T. S., and M. I. Jordan. "Variational Probabilistic Inference and the QMR-DT Network." Journal of Artificial Intelligence Research 10 (May 1, 1999): 291–322. http://dx.doi.org/10.1613/jair.583.

Повний текст джерела

Анотація:

We describe a variational approximation method for efficient inference in large-scale probabilistic models. Variational methods are deterministic procedures that provide approximations to marginal and conditional probabilities of interest. They provide alternatives to approximate inference methods based on stochastic sampling or search. We describe a variational approach to the problem of diagnostic inference in the `Quick Medical Reference' (QMR) network. The QMR network is a large-scale probabilistic graphical model built on statistical and expert knowledge. Exact probabilistic inference is infeasible in this model for all but a small set of cases. We evaluate our variational inference algorithm on a large set of diagnostic test cases, comparing the algorithm to a state-of-the-art stochastic sampling method.

Стилі APA, Harvard, Vancouver, ISO та ін.

23

Plavcan, David, Georg J. Mayr, and Achim Zeileis. "Automatic and Probabilistic Foehn Diagnosis with a Statistical Mixture Model." Journal of Applied Meteorology and Climatology 53, no. 3 (March 2014): 652–59. http://dx.doi.org/10.1175/jamc-d-13-0267.1.

Повний текст джерела

Анотація:

AbstractDiagnosing foehn winds from weather station data downwind of topographic obstacles requires distinguishing them from other downslope winds, particularly nocturnal ones driven by radiative cooling. An automatic classification scheme to obtain reproducible results that include information about the (un)certainty of the diagnosis is presented. A statistical mixture model separates foehn and no-foehn winds in a measured time series of wind. In addition to wind speed and direction, it accommodates other physically meaningful classifiers such as the (potential) temperature difference to an upwind station (e.g., near the crest) or relative humidity. The algorithm was tested for Wipp Valley in the central Alps against human expert classification and a previous objective method (Drechsel and Mayr 2008), which the new method outperforms. Climatologically, using only wind information gives nearly identical foehn frequencies as when using additional covariables. A data record length of at least one year is required for satisfactory results. The suitability of mixture models for objective classification of foehn at other locations will have to be tested in further studies.

Стилі APA, Harvard, Vancouver, ISO та ін.

24

Zdrazilova, Nada, and Martin Krejsa. "Surface Condensation Assessment Using Probabilistic Calculation." Advanced Materials Research 1083 (January 2015): 131–36. http://dx.doi.org/10.4028/www.scientific.net/amr.1083.131.

Повний текст джерела

Анотація:

This paper deals with the use of probabilistic methods in the reliability assessment of water vapor condensation on the building structures surface. To calculate the resulting probability of failure it was used original and newly developed Direct Optimized Probabilistic Calculation – DOProC method, which has been successfully applied in the software system ProbCalc. To solve this probabilistic computation tasks, this would appear to be very effective and accurate. When calculating the resulting probability of failure there was also taken into account the statistical dependence of the random input variables, which were expressed probabilistically based on long-term monitoring of the assessed building.

Стилі APA, Harvard, Vancouver, ISO та ін.

25

Iakushev, Viktor Р., Vladimir M. Bure, Olga А. Mitrofanova, and Evgenii Р. Mitrofanov. "Theoretical foundations of probabilistic and statistical forecasting of agrometeorological risks." Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes 17, no. 2 (2021): 174–82. http://dx.doi.org/10.21638/11701/spbu10.2021.207.

Повний текст джерела

Анотація:

Еach model for forecasting agrometeorological risks based on the analysis of one-dimensional time series is effective for a certain range of initial information. In addition, the values of the initial observations can differ significantly for each specific case, respectively, the widespread use of one method for the analysis of arbitrary information can lead to significant inaccuracies. Thus, the problem of choosing a forecasting method for the initial set of agrometeorological data arises. In this regard, a universal adaptive probabilistic-statistical approach to predicting agrometeorological risks is proposed, which makes it possible to solve the problem of choosing a model. The article presents the results of the first stage of research carried out with the financial support of the Ministry of Education and Science of the Russian Federation a brief overview of the current state of research in this direction is presented, theoretical foundations for predicting agrometeorological risks for a possible onset of drought and frost have been developed, including the task of generating initial information, a description of basic forecasting models, and also a direct description of the proposed approach with a presentation of the general structure of an intelligent system, on the basis of which the corresponding algorithm can be developed and automated as directions for further work.

Стилі APA, Harvard, Vancouver, ISO та ін.

26

LÓPEZ-RUBIO, EZEQUIEL, RAFAEL MARCOS LUQUE-BAENA, and ENRIQUE DOMÍNGUEZ. "FOREGROUND DETECTION IN VIDEO SEQUENCES WITH PROBABILISTIC SELF-ORGANIZING MAPS." International Journal of Neural Systems 21, no. 03 (June 2011): 225–46. http://dx.doi.org/10.1142/s012906571100281x.

Повний текст джерела

Анотація:

Background modeling and foreground detection are key parts of any computer vision system. These problems have been addressed in literature with several probabilistic approaches based on mixture models. Here we propose a new kind of probabilistic background models which is based on probabilistic self-organising maps. This way, the background pixels are modeled with more flexibility. On the other hand, a statistical correlation measure is used to test the similarity among nearby pixels, so as to enhance the detection performance by providing a feedback to the process. Several well known benchmark videos have been used to assess the relative performance of our proposal with respect to traditional neural and non neural based methods, with favourable results, both qualitatively and quantitatively. A statistical analysis of the differences among methods demonstrates that our method is significantly better than its competitors. This way, a strong alternative to classical methods is presented.

Стилі APA, Harvard, Vancouver, ISO та ін.

27

Kann, A., T. Haiden, and C. Wittmann. "Combining 2-m temperature nowcasting and short range ensemble forecasting." Nonlinear Processes in Geophysics 18, no. 6 (December 2, 2011): 903–10. http://dx.doi.org/10.5194/npg-18-903-2011.

Повний текст джерела

Анотація:

Abstract. During recent years, numerical ensemble prediction systems have become an important tool for estimating the uncertainties of dynamical and physical processes as represented in numerical weather models. The latest generation of limited area ensemble prediction systems (LAM-EPSs) allows for probabilistic forecasts at high resolution in both space and time. However, these systems still suffer from systematic deficiencies. Especially for nowcasting (0–6 h) applications the ensemble spread is smaller than the actual forecast error. This paper tries to generate probabilistic short range 2-m temperature forecasts by combining a state-of-the-art nowcasting method and a limited area ensemble system, and compares the results with statistical methods. The Integrated Nowcasting Through Comprehensive Analysis (INCA) system, which has been in operation at the Central Institute for Meteorology and Geodynamics (ZAMG) since 2006 (Haiden et al., 2011), provides short range deterministic forecasts at high temporal (15 min–60 min) and spatial (1 km) resolution. An INCA Ensemble (INCA-EPS) of 2-m temperature forecasts is constructed by applying a dynamical approach, a statistical approach, and a combined dynamic-statistical method. The dynamical method takes uncertainty information (i.e. ensemble variance) from the operational limited area ensemble system ALADIN-LAEF (Aire Limitée Adaptation Dynamique Développement InterNational Limited Area Ensemble Forecasting) which is running operationally at ZAMG (Wang et al., 2011). The purely statistical method assumes a well-calibrated spread-skill relation and applies ensemble spread according to the skill of the INCA forecast of the most recent past. The combined dynamic-statistical approach adapts the ensemble variance gained from ALADIN-LAEF with non-homogeneous Gaussian regression (NGR) which yields a statistical \\mbox{correction} of the first and second moment (mean bias and dispersion) for Gaussian distributed continuous variables. Validation results indicate that all three methods produce sharp and reliable probabilistic 2-m temperature forecasts. However, the statistical and combined dynamic-statistical methods slightly outperform the pure dynamical approach, mainly due to the under-dispersive behavior of ALADIN-LAEF outside the nowcasting range. The training length does not have a pronounced impact on forecast skill, but a spread re-scaling improves the forecast skill substantially. Refinements of the statistical methods yield a slight further improvement.

Стилі APA, Harvard, Vancouver, ISO та ін.

28

Bremnes, John Bjørnar. "Ensemble Postprocessing Using Quantile Function Regression Based on Neural Networks and Bernstein Polynomials." Monthly Weather Review 148, no. 1 (December 27, 2019): 403–14. http://dx.doi.org/10.1175/mwr-d-19-0227.1.

Повний текст джерела

Анотація:

Abstract The value of ensemble forecasts is well documented. However, postprocessing by statistical methods is usually required to make forecasts reliable in a probabilistic sense. In this work a flexible statistical method for making probabilistic forecasts in terms of quantile functions is proposed. The quantile functions are specified by linear combinations of Bernstein basis polynomials, and their coefficients are assumed to be related to ensemble forecasts by means of a highly adaptable neural network. This leads to many parameters to estimate, but a recent learning algorithm often applied to deep-learning problems makes this feasible and provides robust estimates. The method is applied to ~2 yr of ensemble wind speed forecasting data at 125 Norwegian stations for lead time +60 h. An intercomparison with two quantile regression methods shows improvements in quantile skill score of nearly 1%. The most appealing feature of the method is arguably its versatility.

Стилі APA, Harvard, Vancouver, ISO та ін.

29

Viviani, Emma, Luca Di Persio, and Matthias Ehrhardt. "Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case." Energies 14, no. 2 (January 11, 2021): 364. http://dx.doi.org/10.3390/en14020364.

Повний текст джерела

Анотація:

In this work, we investigate a probabilistic method for electricity price forecasting, which overcomes traditional ones. We start considering statistical methods for point forecast, comparing their performance in terms of efficiency, accuracy, and reliability, and we then exploit Neural Networks approaches to derive a hybrid model for probabilistic type forecasting. We show that our solution reaches the highest standard both in terms of efficiency and precision by testing its output on German electricity prices data.

Стилі APA, Harvard, Vancouver, ISO та ін.

30

Viviani, Emma, Luca Di Persio, and Matthias Ehrhardt. "Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case." Energies 14, no. 2 (January 11, 2021): 364. http://dx.doi.org/10.3390/en14020364.

Повний текст джерела

Анотація:

In this work, we investigate a probabilistic method for electricity price forecasting, which overcomes traditional ones. We start considering statistical methods for point forecast, comparing their performance in terms of efficiency, accuracy, and reliability, and we then exploit Neural Networks approaches to derive a hybrid model for probabilistic type forecasting. We show that our solution reaches the highest standard both in terms of efficiency and precision by testing its output on German electricity prices data.

Стилі APA, Harvard, Vancouver, ISO та ін.

31

Balashov, Nikolay V., Anne M. Thompson, and George S. Young. "Probabilistic Forecasting of Surface Ozone with a Novel Statistical Approach." Journal of Applied Meteorology and Climatology 56, no. 2 (February 2017): 297–316. http://dx.doi.org/10.1175/jamc-d-16-0110.1.

Повний текст джерела

Анотація:

AbstractThe recent change in the Environmental Protection Agency’s surface ozone regulation, lowering the surface ozone daily maximum 8-h average (MDA8) exceedance threshold from 75 to 70 ppbv, poses significant challenges to U.S. air quality (AQ) forecasters responsible for ozone MDA8 forecasts. The forecasters, supplied by only a few AQ model products, end up relying heavily on self-developed tools. To help U.S. AQ forecasters, this study explores a surface ozone MDA8 forecasting tool that is based solely on statistical methods and standard meteorological variables from the numerical weather prediction (NWP) models. The model combines the self-organizing map (SOM), which is a clustering technique, with a stepwise weighted quadratic regression using meteorological variables as predictors for ozone MDA8. The SOM method identifies different weather regimes, to distinguish between various modes of ozone variability, and groups them according to similarity. In this way, when a regression is developed for a specific regime, data from the other regimes are also used, with weights that are based on their similarity to this specific regime. This approach, regression in SOM (REGiS), yields a distinct model for each regime taking into account both the training cases for that regime and other similar training cases. To produce probabilistic MDA8 ozone forecasts, REGiS weighs and combines all of the developed regression models on the basis of the weather patterns predicted by an NWP model. REGiS is evaluated over the San Joaquin Valley in California and the northeastern plains of Colorado. The results suggest that the model performs best when trained and adjusted separately for an individual AQ station and its corresponding meteorological site.

Стилі APA, Harvard, Vancouver, ISO та ін.

32

Veshkurtsev, Yu M., and D. A. Titov. "Determination of probabilistic characteristics of random values of estimates of the Lyapunov function when describing a physical process." Metrologiya, no. 4 (December 15, 2021): 53–67. http://dx.doi.org/10.32446/0132-4713.2021-4-53-67.

Повний текст джерела

Анотація:

The applied application of the Lyapunov characteristic function is determined by the properties of its estimates. Probabilistic characteristics of estimates of the Lyapunov characteristic function are described for the first time. The probabilistic characteristics of random values of estimates of the Lyapunov function are empirically estimated using statistical methods. The Matlab package has developed a model of a special device for obtaining estimates of the characteristic function by a direct method. A quasi-deterministic signal is fed to the input of the model, the instantaneous values of which are distributed according to the arcsine law, and an array of values of estimates of the Lyapunov function is obtained at the output, which is used to estimate the probabilistic characteristics of these estimates. Statistical estimation was performed by an indirect method. It is established that the values of the estimates of the Lyapunov characteristic function are distributed according to the normal law. The results of the research will be useful in engineering calculations, for example, when detecting message transmission errors in modems with a modulated characteristic function.

Стилі APA, Harvard, Vancouver, ISO та ін.

33

Hehl, Simon, Till Vallée, Thomas Tannert, and Yu Bai. "A Probabilistic Strength Prediction Method for Adhesively Bonded Joints Composed of Wooden Adherends." Key Engineering Materials 417-418 (October 2009): 533–36. http://dx.doi.org/10.4028/www.scientific.net/kem.417-418.533.

Повний текст джерела

Анотація:

Joining timber structural elements using mechanical fasteners goes against the anisotropic and fibrous nature of the material. Adhesive bonding is by far better adapted, since it permits a smoother load transfer. However, the strength prediction of adhesively bonded wooden joints is difficult brittle nature of the adherends, the complex stress distribution as well as the uncertainties regarding the associated material resistance. As a contribution to help close this research gap, the authors have carried out experimental and analytical investigations on adhesively bonded double lap joints composed of timber. This paper describes the experimental and numerical results and suggests a probabilistic method for the strength prediction of joints composed of brittle adherends and adhesives. The method considers the scale sensitivity of material strength modelled using a Weibull statistical function, and considers both the statistical variation and the size effect in the strength of the material. The probabilistic method presents a mechanical explanation for the increased resistance of local zones subjected to high strain or stress peaks.

Стилі APA, Harvard, Vancouver, ISO та ін.

34

Pérez, Javier, Jose-Luis Guardiola, Alberto J. Perez, and Juan-Carlos Perez-Cortes. "Probabilistic Evaluation of 3D Surfaces Using Statistical Shape Models (SSM)." Sensors 20, no. 22 (November 17, 2020): 6554. http://dx.doi.org/10.3390/s20226554.

Повний текст джерела

Анотація:

Inspecting a 3D object which shape has elastic manufacturing tolerances in order to find defects is a challenging and time-consuming task. This task usually involves humans, either in the specification stage followed by some automatic measurements, or in other points along the process. Even when a detailed inspection is performed, the measurements are limited to a few dimensions instead of a complete examination of the object. In this work, a probabilistic method to evaluate 3D surfaces is presented. This algorithm relies on a training stage to learn the shape of the object building a statistical shape model. Making use of this model, any inspected object can be evaluated obtaining a probability that the whole object or any of its dimensions are compatible with the model, thus allowing to easily find defective objects. Results in simulated and real environments are presented and compared to two different alternatives.

Стилі APA, Harvard, Vancouver, ISO та ін.

35

Lu, Yuanxiang, Sihan Liu, Xinru Zhang, Zeyi Jiang, and Dianyu E. "A Probabilistic Statistical Method for the Determination of Void Morphology with CFD-DEM Approach." Energies 13, no. 16 (August 5, 2020): 4041. http://dx.doi.org/10.3390/en13164041.

Повний текст джерела

Анотація:

Voids that are formed by gas injection in a packed bed play an important role in metallurgical and chemical furnaces. Herein, two-phase gas–solid flow in a two-dimensional packed bed during blast injection was simulated numerically. The results indicate that the void stability was dynamic, and the void shape and size fluctuated within a certain range. To determine the void morphology quantitatively, a probabilistic method was proposed. By statistically analyzing the white probability of each pixel in binary images at multiple times, the void boundaries that correspond to different probability ranges were obtained. The boundary that was most appropriate with the simulation result was selected and defined as the well-matched void boundary. Based on this method, the morphologies of voids that formed at different gas velocities were simulated and compared. The method can help us to express the morphological characteristics of the dynamically stable voids in a numerical simulation.

Стилі APA, Harvard, Vancouver, ISO та ін.

36

Valle, Denis, Benjamin Baiser, Christopher W. Woodall, and Robin Chazdon. "Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method." Ecology Letters 17, no. 12 (October 17, 2014): 1591–601. http://dx.doi.org/10.1111/ele.12380.

Повний текст джерела

Стилі APA, Harvard, Vancouver, ISO та ін.

37

Pitner, P. "Statistical analysis of steam generator tube lifetime and probabilistic method for tube bundle inspection." Reliability Engineering & System Safety 21, no. 4 (January 1988): 271–92. http://dx.doi.org/10.1016/0951-8320(88)90097-x.

Повний текст джерела

Стилі APA, Harvard, Vancouver, ISO та ін.

38

Tvrdá, Katarína. "Probability analysis of an embedded water tank." MATEC Web of Conferences 310 (2020): 00014. http://dx.doi.org/10.1051/matecconf/202031000014.

Повний текст джерела

Анотація:

The design of building structures must fulfil specific regulations, in our case, different building standards, among them Eurocodes. In addition to deterministic procedures in structural design, these standards also allow probabilistic procedures. The embedded tank loaded with soil and liquid is solved by the probability analysis using ANSYS, which contains several probabilistic methods. The reinforced concrete tank is solved by the RSM probabilistic method, which uses the well-known Monte-Carlo method in the background. Input parameters (material properties of soil and reinforced concrete, load - pressure from water, geometric data - change of both wall and tank bottom thickness) are entered into the calculation with certain aberrances allowed by standards in the construction and loading of structures. The results are also sets of probabilistic variables with a certain variance, as opposed to a deterministic calculation, where only one value results. These procedures, which use statistical methods, have been at the forefront in recent decades. At the end of the paper, some results of the analysis of embedded reinforced concrete water tank (deterministic and probabilistic procedure) in state of tank failure on the second limit state are presented.

Стилі APA, Harvard, Vancouver, ISO та ін.

39

Nipen, Thomas N., Greg West, and Roland B. Stull. "Updating Short-Term Probabilistic Weather Forecasts of Continuous Variables Using Recent Observations." Weather and Forecasting 26, no. 4 (August 1, 2011): 564–71. http://dx.doi.org/10.1175/waf-d-11-00022.1.

Повний текст джерела

Анотація:

Abstract A statistical postprocessing method for improving probabilistic forecasts of continuous weather variables, given recent observations, is presented. The method updates an existing probabilistic forecast by incorporating observations reported in the intermediary time since model initialization. As such, this method provides updated short-range probabilistic forecasts at an extremely low computational cost. The method models the time sequence of cumulative distribution function (CDF) values corresponding to the observation as a first-order Markov process. Verifying CDF values are highly correlated in time, and their changes in time are modeled probabilistically by a transition function. The effect of the method is that the spread of the probabilistic forecasts for the first few hours after an observation has been made is considerably narrower than the original forecast. The updated probability distributions widen back toward the original forecast for forecast times far in the future as the effect of the recent observation diminishes. The method is tested on probabilistic forecasts produced by an operational ensemble forecasting system. The method improves the ignorance score and the continuous ranked probability score of the probabilistic forecasts significantly for the first few hours after an observation has been made. The mean absolute error of the median of the probability distribution is also shown to be improved.

Стилі APA, Harvard, Vancouver, ISO та ін.

40

Grana, Dario, and Ernesto Della Rossa. "Probabilistic petrophysical-properties estimation integrating statistical rock physics with seismic inversion." GEOPHYSICS 75, no. 3 (May 2010): O21—O37. http://dx.doi.org/10.1190/1.3386676.

Повний текст джерела

Анотація:

A joint estimation of petrophysical properties is proposed that combines statistical rock physics and Bayesian seismic inversion. Because elastic attributes are correlated with petrophysical variables (effective porosity, clay content, and water saturation) and this physical link is associated with uncertainties, the petrophysical-properties estimation from seismic data can be seen as a Bayesian inversion problem. The purpose of this work was to develop a strategy for estimating the probability distributions of petrophysical parameters and litho-fluid classes from seismics. Estimation of reservoir properties and the associated uncertainty was performed in three steps: linearized seismic inversion to estimate the probabilities of elastic parameters, probabilistic upscaling to include the scale-changes effect, and petrophysical inversion to estimate the probabilities of petrophysical variables andlitho-fluid classes. Rock-physics equations provide the linkbetween reservoir properties and velocities, and linearized seismic modeling connects velocities and density to seismic amplitude. A full Bayesian approach was adopted to propagate uncertainty from seismics to petrophysics in an integrated framework that takes into account different sources of uncertainty: heterogeneity of the real data, approximation of physical models, measurement errors, and scale changes. The method has been tested, as a feasibility step, on real well data and synthetic seismic data to show reliable propagation of the uncertainty through the three different steps and to compare two statistical approaches: parametric and nonparametric. Application to a real reservoir study (including data from two wells and partially stacked seismic volumes) has provided as a main result the probability densities of petrophysical properties and litho-fluid classes. It demonstrated the applicability of the proposed inversion method.

Стилі APA, Harvard, Vancouver, ISO та ін.

41

Worsnop, Rochelle P., Michael Scheuerer, Thomas M. Hamill, and Julie K. Lundquist. "Generating wind power scenarios for probabilistic ramp event prediction using multivariate statistical post-processing." Wind Energy Science 3, no. 1 (June 14, 2018): 371–93. http://dx.doi.org/10.5194/wes-3-371-2018.

Повний текст джерела

Анотація:

Abstract. Wind power forecasting is gaining international significance as more regions promote policies to increase the use of renewable energy. Wind ramps, large variations in wind power production during a period of minutes to hours, challenge utilities and electrical balancing authorities. A sudden decrease in wind-energy production must be balanced by other power generators to meet energy demands, while a sharp increase in unexpected production results in excess power that may not be used in the power grid, leading to a loss of potential profits. In this study, we compare different methods to generate probabilistic ramp forecasts from the High Resolution Rapid Refresh (HRRR) numerical weather prediction model with up to 12 h of lead time at two tall-tower locations in the United States. We validate model performance using 21 months of 80 m wind speed observations from towers in Boulder, Colorado, and near the Columbia River gorge in eastern Oregon. We employ four statistical post-processing methods, three of which are not currently used in the literature for wind forecasting. These procedures correct biases in the model and generate short-term wind speed scenarios which are then converted to power scenarios. This probabilistic enhancement of HRRR point forecasts provides valuable uncertainty information of ramp events and improves the skill of predicting ramp events over the raw forecasts. We compute Brier skill scores for each method with regard to predicting up- and down-ramps to determine which method provides the best prediction. We find that the Standard Schaake shuffle method yields the highest skill at predicting ramp events for these datasets, especially for up-ramp events at the Oregon site. Increased skill for ramp prediction is limited at the Boulder, CO, site using any of the multivariate methods because of the poor initial forecasts in this area of complex terrain. These statistical methods can be implemented by wind farm operators to generate a range of possible wind speed and power scenarios to aid and optimize decisions before ramp events occur.

Стилі APA, Harvard, Vancouver, ISO та ін.

42

Laio, F., and S. Tamea. "Verification tools for probabilistic forecasts of continuous hydrological variables." Hydrology and Earth System Sciences 11, no. 4 (May 3, 2007): 1267–77. http://dx.doi.org/10.5194/hess-11-1267-2007.

Повний текст джерела

Анотація:

Abstract. In the present paper we describe some methods for verifying and evaluating probabilistic forecasts of hydrological variables. We propose an extension to continuous-valued variables of a verification method originated in the meteorological literature for the analysis of binary variables, and based on the use of a suitable cost-loss function to evaluate the quality of the forecasts. We find that this procedure is useful and reliable when it is complemented with other verification tools, borrowed from the economic literature, which are addressed to verify the statistical correctness of the probabilistic forecast. We illustrate our findings with a detailed application to the evaluation of probabilistic and deterministic forecasts of hourly discharge values.

Стилі APA, Harvard, Vancouver, ISO та ін.

43

Laio, F., and S. Tamea. "Verification tools for probabilistic forecasts of continuous hydrological variables." Hydrology and Earth System Sciences Discussions 3, no. 4 (August 8, 2006): 2145–73. http://dx.doi.org/10.5194/hessd-3-2145-2006.

Повний текст джерела

Анотація:

Abstract. In the present paper we describe some methods for verifying and evaluating probabilistic forecasts of hydrological variables. We propose an extension to continuous-valued variables of a verification method originated in the meteorological literature for the analysis of binary variables, and based on the use of a suitable cost-loss function to evaluate the quality of the forecasts. We find that this procedure is useful and reliable when it is complemented with other verification tools, borrowed from the economic literature, which are addressed to verify the statistical correctness of the probabilistic forecast. We illustrate our findings with a detailed application to the evaluation of probabilistic and deterministic forecasts of hourly discharge values.

Стилі APA, Harvard, Vancouver, ISO та ін.

44

Muhammed, Jemal J. "Deterministic and Probabilistic Approaches in the Analysis of the Bearing Capacity of a Bridge Foundation on Undrained Clay Soil." Slovak Journal of Civil Engineering 27, no. 2 (June 1, 2019): 44–51. http://dx.doi.org/10.2478/sjce-2019-0015.

Повний текст джерела

Анотація:

AbstractThis study aims at evaluating deterministic and probabilistic approaches for an analysis of the bearing capacity of a highway bridge foundation on undrained clay soil. The analysis of a rectangular concrete footing was presented for the ultimate strength limit state of the bearing resistance according to the formulation in ES EN 1991:2015 and ERA-Bridge Design Manual, which are the Ethiopian design codes for foundation structures. In the deterministic analysis, the traditional total safety factor method recommended by the ES EN 1991:2015, ERA and AASHTO LRFD method was implemented. It was assumed that design variables such as the soil parameters and loads would follow normal and lognormal distribution functions. With regard to the probabilistic methods, NESSUS-9.8 software, a statistical computer program, was used for the analysis. Comparisons were made between the results obtained from the traditional deterministic method and the reliability-based design approach. The evaluation asserts that the probabilistic approach is a better tool than the deterministic one for assessing the safety and reliability of geotechnical structures. The probabilistic design method rationally accounts for uncertainties more than the conventional deterministic method does. Thus, the author recommends that the National Design Codes of Ethiopia need to be revised and calibrated based on a reliability design format.

Стилі APA, Harvard, Vancouver, ISO та ін.

45

Zapletal, David, and Viera Pacakova. "Statistical Software Packages as an Innovative and Motivational Tool for Teaching Statistics." International Journal of Communications 16 (March 5, 2022): 19–21. http://dx.doi.org/10.46300/9107.2022.16.4.

Повний текст джерела

Анотація:

Based on longtime teaching experience, the authors of the article present some reasons for the unpopularity of statistical disciplines that are taught at the economic faculties. We assume that the statistical software packages could be an effective motivational tool for teaching the statistical methods. Before explaining the individual statistical method, it is suitable to choose data sets which the students find interesting. In such a way it is possible to convince the students about the usefulness of the information provided by this statistical method. Statistical software packages allow a significant innovation of statistical disciplines. The authors present an example of good fitness tests application. The result in the form of a probabilistic model of a random variable provides detailed information of the population, much more extensive than the results of interval estimates and parametric hypotheses tests.

Стилі APA, Harvard, Vancouver, ISO та ін.

46

Khorol’skii, V. Ya, I. V. Atanov, M. A. Mastepanenko, and I. K. Sharipov. "Choice of the Method of Probabilistic Modeling of Statistical Dynamics of Autonomous Power Supply Systems." Russian Electrical Engineering 89, no. 7 (July 2018): 425–27. http://dx.doi.org/10.3103/s1068371218070076.

Повний текст джерела

Стилі APA, Harvard, Vancouver, ISO та ін.

47

Myronchuk, V., Yu Zmievskii, V. Zakharov, and L. Kornienko. "Method for determining the reliability of the probabilistic-statistical model for calculating the ozonation process." Scientific Works of National University of Food Technologies 26, no. 4 (August 2020): 90–97. http://dx.doi.org/10.24263/2225-2924-2020-26-4-11.

Повний текст джерела

Стилі APA, Harvard, Vancouver, ISO та ін.

48

Lawrence, D., E. Paquet, J. Gailhard, and A. K. Fleig. "Stochastic semi-continuous simulation for extreme flood estimation in catchments with combined rainfall–snowmelt flood regimes." Natural Hazards and Earth System Sciences 14, no. 5 (May 23, 2014): 1283–98. http://dx.doi.org/10.5194/nhess-14-1283-2014.

Повний текст джерела

Анотація:

Abstract. Simulation methods for extreme flood estimation represent an important complement to statistical flood frequency analysis because a spectrum of catchment conditions potentially leading to extreme flows can be assessed. In this paper, stochastic, semi-continuous simulation is used to estimate extreme floods in three catchments located in Norway, all of which are characterised by flood regimes in which snowmelt often has a significant role. The simulations are based on SCHADEX, which couples a precipitation probabilistic model with a hydrological simulation such that an exhaustive set of catchment conditions and responses is simulated. The precipitation probabilistic model is conditioned by regional weather patterns, and a bottom–up classification procedure was used to define a set of weather patterns producing extreme precipitation in Norway. SCHADEX estimates for the 1000-year (Q1000) discharge are compared with those of several standard methods, including event-based and long-term simulations which use a single extreme precipitation sequence as input to a hydrological model, statistical flood frequency analysis based on the annual maximum series, and the GRADEX method. The comparison suggests that the combination of a precipitation probabilistic model with a long-term simulation of catchment conditions, including snowmelt, produces estimates for given return periods which are more in line with those based on statistical flood frequency analysis, as compared with the standard simulation methods, in two of the catchments. In the third case, the SCHADEX method gives higher estimates than statistical flood frequency analysis and further suggests that the seasonality of the most likely Q1000 events differs from that of the annual maximum flows. The semi-continuous stochastic simulation method highlights the importance of considering the joint probability of extreme precipitation, snowmelt rates and catchment saturation states when assigning return periods to floods estimated by precipitation-runoff methods. The SCHADEX methodology, as applied here, is dependent on observed discharge data for calibration of a hydrological model, and further study to extend its application to ungauged catchments would significantly enhance its versatility.

Стилі APA, Harvard, Vancouver, ISO та ін.

49

Lawrence, D., E. Paquet, J. Gailhard, and A. K. Fleig. "Stochastic semi-continuous simulation for extreme flood estimation in catchments with combined rainfall-snowmelt flood regimes." Natural Hazards and Earth System Sciences Discussions 1, no. 6 (November 26, 2013): 6785–828. http://dx.doi.org/10.5194/nhessd-1-6785-2013.

Повний текст джерела

Анотація:

Abstract. Simulation methods for extreme flood estimation represent an important complement to statistical flood frequency analysis because a spectrum of catchment conditions potentially leading to extreme flows can be assessed. In this paper, stochastic, semi-continuous simulation is used to estimate extreme floods in three catchments located in Norway, all of which are characterised by flood regimes in which snowmelt often has a significant role. The simulations are based on SCHADEX, which couples a precipitation probabilistic model with a hydrological simulation such that an exhaustive set of catchment conditions and responses are simulated. The precipitation probabilistic model is conditioned by regional weather patterns, and a "bottom-up" classification procedure was used for defining a set of weather patterns producing extreme precipitation in Norway. SCHADEX estimates for the 1000 yr (Q1000) discharge are compared with those of several standard methods, including event-based and long-term simulations which use a single extreme precipitation sequence as input to a hydrological model, with statistical flood frequency analysis based on the annual maximum series, and with the GRADEX method. The comparison suggests that the combination of a precipitation probabilistic model with a long-term simulation of catchment conditions, including snowmelt, produces estimates for given return periods which are more in line with those based on statistical flood frequency analysis, as compared with the standard simulation methods, in two of the catchments. In the third case, the SCHADEX method gives higher estimates than statistical flood frequency analysis and further suggests that the seasonality of the most likely Q1000 events differs from that of the annual maximum flows. The semi-continuous stochastic simulation method highlights the importance of considering the joint probability of extreme precipitation, snowmelt rates and catchment saturation states when assigning return periods to floods estimated by precipitation-runoff methods. The SCHADEX methodology, as applied here, is dependent on observed discharge data for calibration of a hydrological model, and further study to extend its application to ungauged catchments would significantly enhance its versatility.

Стилі APA, Harvard, Vancouver, ISO та ін.

50

Chiabert, Paolo, and Mario Costa. "Statistical Modelling of Nominal and Measured Mechanical Surfaces." Journal of Computing and Information Science in Engineering 3, no. 1 (March 1, 2003): 87–94. http://dx.doi.org/10.1115/1.1569941.

Повний текст джерела

Анотація:

Modern manufacturing processes require unambiguous description of product morphology. In spite of numerous successes in the development of new mathematical tools, there not exists a method providing complete and coherent information on the product shape along its lifecycle. Consequently, industrial methods currently employed in dimensional and geometrical controls do not fully satisfy designers, manufactures and customers. A possible solution could be a statistical description of product shape because it has strong mathematical basis, uses powerful analysis tools and provides a single unifying model along the product development process. The comparison with industrial practice and deterministic mathematical tools in the design, manufacturing and verification phases, shows some interesting advantages of the probabilistic approach. The paper illustrates the theoretical basis of the probabilistic approach, provides the instruments necessary to its implementation and, finally, shows some applications in the inspection of mechanical objects.

Стилі APA, Harvard, Vancouver, ISO та ін.

Статті в журналах з теми "Probabilistic-statistical method"

Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями