On Level Crossings by Gaussian Fields

Statistics ◽  
1985 ◽  
Vol 16 (4) ◽  
pp. 581-596
Author(s):  
U. Zähle
Keyword(s):  
Gaussian Fields ◽  
Level Crossings

Distribution of Speed and Acceleration on a Tread Wear Course

1981 ◽  
Vol 9 (1) ◽  
pp. 19-25 ◽  
Author(s):  
G. S. Ludwig ◽  
F. C. Brenner
Keyword(s):  
Traffic Safety ◽  
Highway Traffic ◽  
National Highway Traffic Safety ◽  
Level Crossings ◽  
Acceleration Level ◽  
Longitudinal Acceleration ◽  
Acceleration Data ◽  
National Highway

Abstract Belted bias and radial Course Monitoring Tires were run over the National Highway Traffic Safety Administration tread wear course at San Angelo on a vehicle instrumented to measure lateral and longitudinal accelerations, speed, and number of wheel rotations. The data were recorded as histograms. The distribution of speed, the distributions of lateral and longitudinal acceleration, and the number of acceleration level crossings are given. Acceleration data for segments of the course are also given.

Multi-criteria FUCOM-MAIRCA model for the evaluation of level crossings: case study in the Republic of Serbia

2019 ◽  
Vol 1 (1) ◽  
pp. 108-129 ◽  
Author(s):  
Dragan Pamučar ◽  
◽  
Vesko Lukovac ◽  
Darko Božanić ◽  
Nenad Komazec ◽  
...  
Keyword(s):  
Level Crossings ◽  
The Republic

Extrema and Level Crossings of x(2) Processes.

1985 ◽  
Author(s):  
Michael Aronowich ◽  
Robert J. Adler
Keyword(s):  
Level Crossings

scholarly journals Evaluation of Safety Degree at Railway Crossings in Order to Achieve Sustainable Traffic Management: A Novel Integrated Fuzzy MCDM Model

2021 ◽  
Vol 13 (2) ◽  
pp. 832
Author(s):  
Aleksandar Blagojević ◽  
Sandra Kasalica ◽  
Željko Stević ◽  
Goran Tričković ◽  
Vesna Pavelkić
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Assessment Model ◽  
Level Crossings ◽  
Fuzzy Matrix ◽  
Sustainable Performance ◽  
Current State ◽  
Criterion Weight ◽  
Railway System ◽  
Criteria Importance

Sustainable traffic system management under conditions of uncertainty and inappropriate road infrastructure is a responsible and complex task. In Bosnia and Herzegovina (BiH), there is a large number of level crossings which represent potentially risky places in traffic. The current state of level crossings in BiH is a problem of the greatest interest for the railway and a generator of accidents. Accordingly, it is necessary to identify the places that are currently a priority for the adoption of measures and traffic control in order to achieve sustainability of the whole system. In this paper, the Šamac–Doboj railway section and passive level crossings have been considered. Fifteen different criteria were formed and divided into three main groups: safety criteria, road exploitation characteristics, and railway exploitation characteristics. A novel integrated fuzzy FUCOM (full consistency method)—fuzzy PIPRECIA (pivot pairwise relative criteria importance assessment) model was formed to determine the significance of the criteria. When calculating the weight values of the main criteria, the fuzzy Heronian mean operator was used for their averaging. The evaluation of level crossings was performed using fuzzy MARCOS (measurement of alternatives and ranking according to compromise solution). An original integrated fuzzy FUCOM–Fuzzy PIPRECIA–Fuzzy MARCOS model was created as the main contribution of the paper. The results showed that level crossings 42 + 690 (LC4) and LC8 (82 + 291) are the safest considering all 15 criteria. The verification of the results was performed through four phases of sensitivity analysis: resizing of an initial fuzzy matrix, comparative analysis with other fuzzy approaches, simulations of criterion weight values, and calculation of Spearman’s correlation coefficient (SCC). Finally, measures for the sustainable performance of the railway system were proposed.

scholarly journals Sufficiency of a Gaussian power spectrum likelihood for accurate cosmology from upcoming weak lensing surveys

2021 ◽  
Author(s):  
Robin E Upham ◽  
Michael L Brown ◽  
Lee Whittaker
Keyword(s):  
Power Spectrum ◽  
Random Noise ◽  
Power Spectra ◽  
Stage Iv ◽  
Wishart Distribution ◽  
Weak Lensing ◽  
Dependence Structure ◽  
Gaussian Fields ◽  
Non Gaussian ◽  
Parameter Constraints

Abstract We investigate whether a Gaussian likelihood is sufficient to obtain accurate parameter constraints from a Euclid-like combined tomographic power spectrum analysis of weak lensing, galaxy clustering and their cross-correlation. Testing its performance on the full sky against the Wishart distribution, which is the exact likelihood under the assumption of Gaussian fields, we find that the Gaussian likelihood returns accurate parameter constraints. This accuracy is robust to the choices made in the likelihood analysis, including the choice of fiducial cosmology, the range of scales included, and the random noise level. We extend our results to the cut sky by evaluating the additional non-Gaussianity of the joint cut-sky likelihood in both its marginal distributions and dependence structure. We find that the cut-sky likelihood is more non-Gaussian than the full-sky likelihood, but at a level insufficient to introduce significant inaccuracy into parameter constraints obtained using the Gaussian likelihood. Our results should not be affected by the assumption of Gaussian fields, as this approximation only becomes inaccurate on small scales, which in turn corresponds to the limit in which any non-Gaussianity of the likelihood becomes negligible. We nevertheless compare against N-body weak lensing simulations and find no evidence of significant additional non-Gaussianity in the likelihood. Our results indicate that a Gaussian likelihood will be sufficient for robust parameter constraints with power spectra from Stage IV weak lensing surveys.

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