Gravitational Evolution of the Large‐Scale Probability Density Distribution: The Edgeworth and Gamma Expansions

2000 ◽  
Vol 539 (2) ◽  
pp. 522-531 ◽  
Author(s):  
E. Gaztanaga ◽  
P. Fosalba ◽  
E. Elizalde
Keyword(s):  
Density Distribution ◽  
Probability Density ◽  
Large Scale ◽  
Probability Density Distribution ◽  
Scale Probability

scholarly journals Influence Assessment of the Information Concerning the Bearing Type of Axle Box of Cars on the Automatic Classification Accuracy of Heated Boxes

2021 ◽  
pp. 5-14
Author(s):  
V. V Burchenkov
Keyword(s):  
Density Distribution ◽  
Probability Density ◽  
Heating Temperature ◽  
Threshold Value ◽  
Probability Density Distribution ◽  
Practical Implementation ◽  
System Of Equations ◽  
Average Value ◽  
Optimal Thresholds ◽  
Different Types

Purpose. The main purpose of the work is to determine and classify the heated cars’ boxes based on the probability of appearance of roller and cassette type boxes in the classes of heated and overheated boxes, as well as the laws of probability density distribution of the recognition signs of normally heated and overheated roller and cassette type boxes. Methodology. The operation features of freight cars with cassette type axle boxes with increased operating heating have been investigated. The methodology of assessing the probability of recognition errors was proposed, which takes into account the fact that sets of normally heated and overheated boxes consist of subsets of boxes with different types of bearings. A system of equations is obtained, the roots of which represent еру values that minimize the recognition probability of the errors of the heated boxes. Findings. It was found out that with some methods of determining the bearing type, for example, by the average value of the ranges of thermal image for each car, the probability of erroneous selection may depend on the probability density distribution of the sign for bearings of different types and the threshold value of this sign. The optimal thresholds for detecting the overheated roller boxes in comparison with the optimal thresholds for detecting overheated cassette boxes were determined. It has been established that the pass of an overheated cassette bearing, provided that the type of bearing is determined correctly, is less likely to lead to an accident than if the cassette box is classified as a roller box. The rejection criteria of axle boxes according to their heating temperature difference on one of the wheel set axis for three variants of settings of the alarm system according to an arrangement of multipurpose complexes of technical means (CTM) were formulated. The practical implementation of this method of adjusting the CTM settings for the Minsk branch of the Belarusian Railways was demonstrated. Originality. A system of equations is obtained, which allows finding the optimal values of temperature thresholds for the detection of overheated roller and cassette boxes under the assumption that the error probabilities in the selection of boxes by their types are known and constant. Practical value. The developed method of adjusting the alarm settings of CTM makes it possible to significantly reduce unjustified train delays and the number of car uncouplings.

scholarly journals A New Modeling Approach for the Probability Density Distribution Function of Wind power Fluctuation

2019 ◽  
Vol 11 (19) ◽  
pp. 5512 ◽  
Author(s):  
Lingzhi Wang ◽  
Jun Liu ◽  
Fucai Qian
Keyword(s):  
Distribution Function ◽  
Density Distribution ◽  
Probability Density ◽  
Wind Power ◽  
Rapid Development ◽  
Probability Density Distribution ◽  
Power Fluctuation ◽  
Function Model ◽  
New Model ◽  
Fireworks Algorithm

With the rapid development of grid-connected wind power, analysing and describing the probability density distribution characteristics of wind power fluctuation has always been a hot and difficult problem in the wind power field. In traditional methods, a single distribution function model is used to fit the probability density distribution of wind power output fluctuation; however, the results are unsatisfying. Therefore, a new distribution function model is proposed in this work for fitting the probability density distribution to replace a single distribution function model. In form, the new model includes only four parameters which make it easier to implement. Four statistical index models are used to evaluate the distribution function fits with the measured probability data. Simulations are designed to compare the new model with the Gaussian mixture model, and results illustrate the effectiveness and advantages of the newly developed model in fitting the wind power fluctuation probability density distribution. Besides, the fireworks algorithm is adopted for determining the optimal parameters in the distribution function model. The comparison experiments of the fireworks algorithm with the particle swarm optimization (PSO) algorithm and the genetic algorithm (GA) are carried out, which shows that the fireworks algorithm has faster convergence speed and higher accuracy than the two common intelligent algorithms, so it is useful for optimizing parameters in power systems.

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