Removal of meteorological effects from meson-telescope data

1969 ◽  
Vol 47 (14) ◽  
pp. 1429-1433 ◽  
Author(s):  
R. M. Briggs ◽  
R. B. Hicks ◽  
S. Standil
Keyword(s):  
Regression Analysis ◽  
Least Squares ◽  
Neutron Monitor ◽  
Ground Level ◽  
Barometric Pressure ◽  
Practical Method ◽  
Meteorological Conditions ◽  
Hourly Data ◽  
Meteorological Effects

Hourly data from a meson mega-telescope have been correlated with the local barometric pressure, the ground-level temperature, and with intensity variations as observed by a distant neutron monitor. Two techniques are considered, viz. a vector least-squares analysis and an hourly regression analysis, the latter being suggested as a practical method whereby stations without radiosonde information may correct their hourly meson data for changing meteorological conditions.

ATMOSPHERIC CONTRIBUTION TO THE DIURNAL VARIATION OF THE COSMIC-RAY MESON INTENSITY AT DEEP RIVER

1966 ◽  
Vol 44 (6) ◽  
pp. 1329-1347 ◽  
Author(s):  
M. Bercovitch
Keyword(s):  
Diurnal Variation ◽  
Neutron Monitor ◽  
Cosmic Ray ◽  
Ground Level ◽  
Barometric Pressure ◽  
Atmospheric Temperature ◽  
The Mean ◽  
Variation Vector ◽  
Best Fit ◽  
Ground Level Air

We have established the correlation between the atmospheric temperature contribution to the diurnal variation observed by a meson monitor at Deep River and the diurnal variation of two easily and continuously observable atmospheric variables, the ground-level air temperature and the barometric pressure. The atmospheric meson diurnal variation vector is taken to be, on a statistical basis, A = M−RN, where M and N represent the observed meson-monitor and neutron-monitor diurnal variations and R is the factor of proportionality between the meson and neutron monitor responses to the primary anisotropy. It is found that A is proportional in amplitude to T, the ground-level temperature diurnal variation, and, further, that T and the barometric-pressure diurnal variation P are proportional in amplitude. The "best-fit" representation of A in terms of T and P is determined by minimizing the mean-square deviation between the daily vectors RN and (M−A). Where A = CtT + CpP, the best fit occurs when Ct = −0.0052%/ °C, Cp = 0.038%/mb, R = 0.47, and the phase of T is shifted by + 1.0 hour. These values apply to Deep River, where the original hourly meson data have been barometer-corrected using a coefficient of 0.16%/mb.

scholarly journals Ozone Concentration at Ground Level Depending on the Content of NOx and Meteorological Conditions

2015 ◽  
Vol 22 (4) ◽  
pp. 527-541 ◽  
Author(s):  
Robert Kalbarczyk ◽  
Eliza Kalbarczyk ◽  
Irena Niedźwiecka-Filipiak ◽  
Liliana Serafin
Keyword(s):  
Cluster Analysis ◽  
Regression Analysis ◽  
Atmospheric Pressure ◽  
Tropospheric Ozone ◽  
Ground Level ◽  
Meteorological Conditions ◽  
Air Quality Assessment ◽  
Ambiguous Effect ◽  
And Cluster Analysis ◽  
The Relationship

Abstract This study analyzed the temporal variation of tropospheric ozone (O3) in Poznan (midwestern Poland) on the basis of data collected from a State Environmental Monitoring air quality assessment station. The aim was to investigate the distribution and variation of O3 levels and to assess the relationship with nitrogen oxides (NOx) and meteorological conditions. These relationships were assessed by multiple regression analysis and cluster analysis. The O3 levels showed a high annual, seasonal and daily volatility, and were significantly influenced by meteorological conditions and NOx levels. High O3 levels were accompanied by above-average levels of radiation (Rad), air temperature (Ta) and wind speed (Ws), together with below-average values of NOx and humidity (Rh). Atmospheric pressure (Ph) had an ambiguous effect on O3 levels.

International association meetings

2017 ◽  
Vol 24 (3) ◽  
pp. 218-233 ◽  
Author(s):  
Susana Cró ◽  
António Miguel Martins
Keyword(s):  
Regression Analysis ◽  
Least Squares ◽  
Host Country ◽  
International Association ◽  
Ordinary Least Squares ◽  
Travel And Tourism ◽  
Meeting Planners ◽  
Competitiveness Index ◽  
Destination Management Organizations ◽  
Selection Of

The aim of our study is to discuss whether the key frequently identified destination attributes desired by associations and meeting planners determine the number of association meetings organized by each country in 2014. Regression analysis was used by ordinary least squares for the number of association meetings organized in 2014 by each country that shows the importance of 12 countries’ destination attributes reported in the meetings, incentives, conventions and events/exhibitions sector literature and included in the travel and tourism competitiveness index. Our study contributes to the literature in two ways: (i) to identify and evaluate the key attributes in the attraction of association meetings (until now dispersed) and (ii) empirically test the importance of these attributes in the selection of meeting host country. From a practical perspective, these findings give valuable information for destination management organizations and meeting planners about the factors that should be improved in each country in order to be selected more often in the organization of those events.

scholarly journals REGRESSION ANALYSIS APPLICATION FOR TELETRAFFIC THEORY TASKS

T-Comm ◽  
2020 ◽  
Vol 14 (12) ◽  
pp. 18-25
Author(s):  
Alina A. Sherstneva ◽  
Keyword(s):  
Regression Analysis ◽  
Least Squares ◽  
Experimental Analysis ◽  
Random Sequence ◽  
Measurement Data ◽  
Real Data ◽  
Polynomial Model ◽  
Theoretical Research ◽  
Graphical Form ◽  
Trend Forecasting

The article aims to consider least squares approach for solving problems of queuing systems theory. The opportunity of predicting the behavior of infocommunication system is shown. Choosing the optimal model of its functioning is proposed. On base monitoring system metrics, statistical data were formed. The article proposes to make data trend forecasting, to estimate parameters of random processes over time. To obtain the results of functioning data in infocommunication systems that are as close as possible to the real values, polynomial and sine models are considered. The method of regression analysis is proposed to determine the parameter values for a model from a set of observational data. In theoretical research, the linear and nonlinear least squares methods are used in terms of a circle. The task of experimental analysis is to obtain an estimated parameter of sine, polynomial models and the center of circle. Experimental analysis was performed using the mathematical modeling program Matlab. A uniformly distributed random sequence and a random sequence with normal distribution are generated. The sequence with experimental data for polynomial and sine models, respectively, are calculated. The correspondence each model for generated data is shown in graphical form. The measurement data obeys observations. The estimated parameters are summarized in the tables. The polynomial order is estimated. The estimated dispersion curve of the polynomial model is obtained. The calculated variance values of the polynomial model are presented. Data trend forecasting for measurement data is made. The estimated values are extremally close to real data. The results are shown in graphs. Finally, an approximate model of the circumference of measurement data is presented in graphical form. After some iterations with estimated center from the arithmetic mean the new circle center is given. And quite close values for center and radius of circle are obtained.

scholarly journals REGRESSION ANALYSIS OF THE COEFFICIENTS OF THE LOSS OF VIBRATIONAL ENERGY WHEN CALCULATING THE NOISE FROM OSSETIAN AND BORING MACHINES

Akustika ◽  
2019 ◽  
Vol 34 ◽  
pp. 95-99
Author(s):  
Alexander Shashurin ◽  
Marat Goguadze ◽  
Alexander Chukarin
Keyword(s):  
Regression Analysis ◽  
Energy Loss ◽  
Least Squares ◽  
Natural Frequencies ◽  
Vibrational Energy ◽  
Regression Coefficient ◽  
Geometric Mean ◽  
Loss Coefficient ◽  
Method Of Least Squares ◽  
Boring Machines

The purpose of this analysis is to approximate the analytical dependences which allow to calculate the vibrational energy loss coefficient at any frequency when calculating the noise from the axle lathe and boring machines. A regression analysis was conducted using the method of least squares. The paper presents the results of the regression coefficient calculations. The dependences obtained allow us to determine the loss coefficient value not only at the geometric mean frequencies of the octave spectrum, but also at the natural frequencies of oscillations.

Sign in / Sign up

Export Citation Format

Share Document