Study on Forecasting the OD Volume of Railway Luggage and Parcel

2011 ◽  
Vol 105-107 ◽  
pp. 1280-1283
Author(s):  
Xue Fei Li ◽  
Mao Xiang Lang
Keyword(s):  
Least Squares ◽  
Gravity Model ◽  
Statistical Data ◽  
Least Squares Method ◽  
High Accuracy ◽  
Gray Model ◽  
Sample Data

The OD volume of railway luggage and parcel on Beijing-Guangzhou Corridor is forecasted by using the gray model and the gravity model. According to the historical statistical data, firstly the sending and arrival volume of railway luggage and parcel of the major cities on Beijing-Guangzhou Corridor is forecasted by applying the gray model and it takes the Beijing volume of railway luggage and parcel for example to show the calculative process. Secondly, by using the least squares method to calibrate the sample data, obtain the value of each coefficient to be determined, get the calibrated gravity model and then the OD volume of railway luggage and parcel is forecasted by adopting the gravity model. Finally the rationality of the forecasting results is analyzed and the forecasting results which can be used in the railway luggage and parcel organization work have a high accuracy and meet the actual needs.

scholarly journals Econometric Analysis of Dynamics of Personnel Training in Tourism Sphere

2021 ◽  
Vol 12 (6) ◽  
pp. 1389-1396
Author(s):  
Anar Eminov Et al.
Keyword(s):  
Least Squares ◽  
Statistical Data ◽  
Least Squares Method ◽  
Tourism Industry ◽  
Econometric Analysis ◽  
Steady Increase ◽  
Foreign Nationals ◽  
Tourism Sector ◽  
Analysis Of Dynamics ◽  
The Relationship

According to the statistical data of recent years, tourism has been one of the ever-growing sectors in Azerbaijan. Thus, in the last five years, there has been a steady increase in the number of entrepreneurship subjects serving tourism in Azerbaijan and the number of foreign nationals traveling for tourism, correspondingly 4.5 and 8.5 percent. At present, the direct share of the tourism industry in the country's GDP and employment is 4.5 and 3.3 percent, respectively. In the article econometric analysis of the dependence on the relationship between tourism industry graduates and their development has been done. The regression equation of the dependence of the number of graduates studying tourism on the number of tourists in the country and the dependence of the tourism sector’s GDP on the number of graduates in the tourism sector were estimated using the Eviews software based on 2008–2017 statistical data using the least squares method.

Application of Legendre Polynomial in Predicting Total Energy Consumption

2015 ◽  
Vol 713-715 ◽  
pp. 1627-1630
Author(s):  
Hong Qin Zhang ◽  
Lai Bin Gao
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Least Squares ◽  
Legendre Polynomial ◽  
Statistical Data ◽  
Least Squares Method ◽  
Total Energy Consumption ◽  
Least Squares Fitting ◽  
Fitting Method

Based on statistical data of National Statistical Bureau of China, and given the least-squares fitting of Legendre polynomial, the data of total energy consumption from 1978 to 2012 is analyzed by least squares method and Legendre polynomial least squares method respectively. The results showed that Legendre polynomial least squares fitting method is excellent and the data of total energy consumption from 2013 to 2016 is predicted by this method.

scholarly journals Technical Note: Review of methods for linear least-squares fitting of data and application to atmospheric chemistry problems

2008 ◽  
Vol 8 (2) ◽  
pp. 6409-6436 ◽  
Author(s):  
C. A. Cantrell
Keyword(s):  
Least Squares ◽  
Atmospheric Chemistry ◽  
Least Squares Method ◽  
Technical Note ◽  
Routine Practice ◽  
Data Sets ◽  
Straight Line ◽  
Sample Data ◽  
Straight Lines ◽  
Best Fit

Abstract. The representation of data, whether geophysical observations, numerical model output or laboratory results, by a best fit straight line is a routine practice in the geosciences and other fields. While the literature is full of detailed analyses of procedures for fitting straight lines to values with uncertainties, a surprising number of scientists blindly use the standard least squares method, such as found on calculators and in spreadsheet programs, that assumes no uncertainties in the x values. Here, the available procedures for estimating the best fit straight line to data, including those applicable to situations for uncertainties present in both the x and y variables, are reviewed. Representative methods that are presented in the literature for bivariate weighted fits are compared using several sample data sets, and guidance is presented as to when the somewhat more involved iterative methods are required, or when the standard least-squares procedure would be expected to be satisfactory. A spreadsheet-based template is made available that employs one method for bivariate fitting.

scholarly journals Experimentalanalytical identification of a mathematical model of a dc motor using the least squares method

2019 ◽  
Vol 21 (4) ◽  
pp. 113-122
Author(s):  
N. A. Malev ◽  
A. I. Mukhametshin ◽  
O. V. Pogoditsky ◽  
A. G. Gorodnov
Keyword(s):  
Mathematical Model ◽  
Least Squares ◽  
Least Squares Method ◽  
Dynamic Properties ◽  
Dc Motor ◽  
High Accuracy ◽  
Electrical Machines ◽  
Analytical Assessment ◽  
Approximate Polynomial ◽  
Process Graphs

The urgency of the problem lies in the formation of mathematical models of electromechanical converters corresponding to the objects of study with high accuracy. An experimental-analytical assessment of transient modes of a DC motor based on an installation for the study of electrical machines has been carried out. Based on the results obtained, an approximation of transient process graphs was carried out using the least squares method and an approximate polynomial of the corresponding order was selected with the closest imminence to the dynamic properties of the object under study.

scholarly journals Technical Note: Review of methods for linear least-squares fitting of data and application to atmospheric chemistry problems

2008 ◽  
Vol 8 (17) ◽  
pp. 5477-5487 ◽  
Author(s):  
C. A. Cantrell
Keyword(s):  
Least Squares ◽  
Atmospheric Chemistry ◽  
Least Squares Method ◽  
Technical Note ◽  
Routine Practice ◽  
Data Sets ◽  
Straight Line ◽  
Sample Data ◽  
Straight Lines ◽  
Best Fit

Abstract. The representation of data, whether geophysical observations, numerical model output or laboratory results, by a best fit straight line is a routine practice in the geosciences and other fields. While the literature is full of detailed analyses of procedures for fitting straight lines to values with uncertainties, a surprising number of scientists blindly use the standard least-squares method, such as found on calculators and in spreadsheet programs, that assumes no uncertainties in the x values. Here, the available procedures for estimating the best fit straight line to data, including those applicable to situations for uncertainties present in both the x and y variables, are reviewed. Representative methods that are presented in the literature for bivariate weighted fits are compared using several sample data sets, and guidance is presented as to when the somewhat more involved iterative methods are required, or when the standard least-squares procedure would be expected to be satisfactory. A spreadsheet-based template is made available that employs one method for bivariate fitting.

A Discrete Data Fitting Models Fusing Genetic Algorithm

2011 ◽  
Vol 267 ◽  
pp. 427-432
Author(s):  
Tong Rang Fan ◽  
Yong Bin Zhao ◽  
Lan Wang
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Discrete Distribution ◽  
Data Fitting ◽  
Small Sample ◽  
Load Testing ◽  
Accurate Data ◽  
Sample Data ◽  
Testing Data ◽  
Dynamic Measuring

To address problems of Least squares method (LSM) fitting curves in application domains, the essay attempts to build a new model by using LMS (Least Median Squares) to analyze the error points, and pretreating the dynamic measuring errors and then getting the fitting curves of testing data. This model is used for electromotor parameters testing which includes load testing and unload testing. Experiments show that the model can erase the influence of outline points, while improving the effects of data curve fitting and reflecting the characteristic of the motor, provide more accurate data fitting curve with small sample data that is in discrete distribution compared with Least squares method.

Application on Network Traffic Prediction Based on Least Squares Support Vector Machine

2010 ◽  
Vol 20-23 ◽  
pp. 364-369 ◽  
Author(s):  
Yu Zhuo Ren ◽  
Ke Wen Xia ◽  
Yan Wang ◽  
Jun Shi
Keyword(s):  
Support Vector Machine ◽  
Least Squares ◽  
Network Traffic ◽  
High Accuracy ◽  
Traffic Model ◽  
Traffic Prediction ◽  
Support Vector ◽  
Actual Application ◽  
Sample Data ◽  
Network Traffic Model

The network traffic is one of the important metrics for describing network behaviors, it plays an important role in network design, network protocol and traffic project implementation. In order to solve some problems in network traffic prediction, according to actual data for network- monitoring traffic, an approach to network traffic prediction is presented based on least squares support vector machine (LS-SVM), it mainly includes selecting for sample data of network traffic, normalization processing of data, network traffic model trained by LS-SVM and network traffic prediction, etc. Actual application results indicate that the method of network traffic prediction has high accuracy and good feasibility.

ESTIMATION OF PARAMETERS OF ECONOMIC GROWTH AUTOREGRESSIVE MODELS

2021 ◽  
Vol 1 (195) ◽  
pp. 33-37
Author(s):  
D.V. Ivanov ◽  
Keyword(s):  
Economic Growth ◽  
Differential Equations ◽  
Least Squares ◽  
Statistical Data ◽  
Least Squares Method ◽  
Growth Models ◽  
Estimation Of Parameters ◽  
Additive Interference ◽  
Constant Coefficients ◽  
Economic Growth Models

The construction of time series models based on statistical data is one of the central tasks of modern econometric studies. Numerous economic models based on differential equations are used to explain the patterns of economic growth. The article is devoted to the estimation of parameters of economic growth models based on solutions of homogeneous differential equations with constant coefficients. A comparative analysis of methods for estimating the parameters of autoregression of economic dynamics series with additive interference in the output signal is carried out. The simulation results showed that the full least squares method gives the most accurate estimates. The most commonly used least squares method gives the worst estimates.

Simulation Test Research of Using the Ritchey-Commom Method for the Detection of Large Flat Mirror

2012 ◽  
Vol 430-432 ◽  
pp. 1733-1737
Author(s):  
Shuo Zhu ◽  
Xiao Hui Zhang
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
High Accuracy ◽  
Influence Functions ◽  
Simulation Test ◽  
Accuracy Measurement ◽  
Compressed Images ◽  
Flat Mirror ◽  
High Accuracy Measurement

In the detection of large flat mirror, the Ritchey-Common test can achieve high accuracy measurement. A method which expands the compressed images due to Ritchey Angle and rotates the plane under test is presented, achieve two sets of influence functions through this we can built two equations according to two different angular positions, we can solve the equations by least squares method. Then through fitting the coefficients, we can get the flat errors ,this paper describe the simulation test of the method in order to prove the feasibility and reliability of this method.

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