Forecast and Control for the Amount of Rural Economic Crops

2014 ◽  
Vol 687-691 ◽  
pp. 4857-4860
Author(s):  
Wen Xi Duan
Keyword(s):  
Least Squares ◽  
Linear Function ◽  
Statistical Methods ◽  
Historical Data ◽  
Least Squares Method ◽  
The Real ◽  
Straight Line ◽  
Line Equation ◽  
And Control

The planting amount is determined by farmers according to the profit of planting economic crops. Moreover, the planting profit is estimated by using the statistical methods. The relation between the planting amount and the profit is similar to a linear function. However, the straight line equation has been set by using the historical data, calculating the slope of the straight line or adopting the least squares method. Therefore, the planting amount in next year will be calculated based on the equation. In a word, the planting amount in next year will be adjusted and controlled on the basis of the calculated planting amount and the real demand in the market.

Theoretical accuracy of the last squares method in the isotope dilution analysis

1984 ◽  
Vol 49 (4) ◽  
pp. 805-820
Author(s):  
Ján Klas
Keyword(s):  
Least Squares ◽  
Isotope Dilution ◽  
Least Squares Method ◽  
Isotope Dilution Analysis ◽  
Straight Line ◽  
The One ◽  
Two Parameter ◽  
Theoretical Accuracy

The accuracy of the least squares method in the isotope dilution analysis is studied using two models, viz a model of a two-parameter straight line and a model of a one-parameter straight line.The equations for the direct and the inverse isotope dilution methods are transformed into linear coordinates, and the intercept and slope of the two-parameter straight line and the slope of the one-parameter straight line are evaluated and treated.

A modified tangent-gas approximation for two-dimensional steady flow

1958 ◽  
Vol 4 (6) ◽  
pp. 600-606 ◽  
Author(s):  
G. Power ◽  
P. Smith
Keyword(s):  
Least Squares ◽  
Steady Flow ◽  
Variational Approach ◽  
Least Squares Method ◽  
Two Dimensional ◽  
Subsonic Flows ◽  
Von Karman ◽  
Straight Line ◽  
Volume Relationship ◽  
Pressure Volume Relationship

A set of two-dimensional subsonic flows past certain cylinders is obtained using hodograph methods, in which the true pressure-volume relationship is replaced by various straight-line approximations. It is found that the approximation obtained by a least-squares method possibly gives best results. Comparison is made with values obtained by using the von Kármán-Tsien approximation and also with results obtained by the variational approach of Lush & Cherry (1956).

A Direct Least Squares Method for Camera Pose Estimation Based on Straight Line Segment Correspondences

2015 ◽  
Vol 35 (6) ◽  
pp. 0615003
Author(s):  
李鑫 Li Xin ◽  
张跃强 Zhang Yueqiang ◽  
刘进博 Liu Jinbo ◽  
张小虎 Zhang Xiaohu ◽  
于起峰 Yu Qifeng
Keyword(s):  
Least Squares ◽  
Pose Estimation ◽  
Line Segment ◽  
Least Squares Method ◽  
Straight Line Segment ◽  
Camera Pose Estimation ◽  
Straight Line ◽  
Camera Pose

Comparison of Faddeev Method and Resonating Group Method above Breakup Threshold

1975 ◽  
Vol 30 (3) ◽  
pp. 271-273 ◽  
Author(s):  
F. Söhre ◽  
E. W. Schmid
Keyword(s):  
Phase Shift ◽  
Least Squares ◽  
Least Squares Method ◽  
Group Method ◽  
Breakup Threshold ◽  
The Real ◽  
Yamaguchi Potential ◽  
Three Body

Abstract The reliability of the resonating group method is studied above the three-body breakup threshold. In particular, the real part of the elastic n-d phase shift is calculated in a model of three spinless bosons interacting by a separable Yamaguchi potential for which exact Faddeev results are available. Spurious singularities which are caused by the distortion part of the resonating group ansatz are eliminated by a least squares 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 Interpretation of the results of monitoring of the piezometric measurements of the Chańcza dam in 2014–2017

2019 ◽  
Vol 42 (1) ◽  
pp. 117-123
Author(s):  
Stanisław K. Lach
Keyword(s):  
Least Squares ◽  
Water Level ◽  
Linear Function ◽  
Least Squares Method ◽  
Atmospheric Precipitation ◽  
Statistical Test ◽  
Water Levels ◽  
Hydraulic Connection ◽  
Control Devices ◽  
The Town

Abstract The occurrence of a hydraulic connection between piezometers is identified based on similar changes in water levels. Some piezometers react to changing upper or lower water levels, some may also react to atmospheric precipitation. If the reaction to variable upper water levels is significant, then leakage of seepage control devices is identified and the dam is subjected to repair works. The aim of this research paper is to present and analyse the dynamics of variability of water levels in open piezometers of the Chańcza dam, located at the 36 km of the Czarna Staszowska River in the town of Korytnica in Świętokrzyskie province (Poland). Before the analysis of the piezometric data was commenced, the Grubbs statistical test was used to identify and reject the outliers. The scope of the research includes the data captured between January 14, 2014 and January 13, 2017. A hypothesis was formulated that the change in the trend occurred after the spring of 2015 when the water level in the reservoir was reduced by approx. 1.5 m. Two trend lines were adapted for the water levels of each piezometer using the least squares method – the first one for the period from January 2014 to May 2015, and the second one from June 2015 to January 2017. In this way, two slopes of the linear function were obtained together with an estimation of their errors. These slopes were compared using a statistical parallelism test.

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.

scholarly journals Classification and Evolution Analysis of Key Transportation Technologies Based on Bibliometrics

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Hua Chen ◽  
Ming Cai ◽  
Ke Huang ◽  
Shuxin Jin
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Gaussian Mixture ◽  
Annual Number ◽  
Bibliometric Method ◽  
Simulation Techniques ◽  
Key Technologies ◽  
Number Of Publications ◽  
And Control ◽  
Transportation Technologies

To study the classification and evolution of key technologies in the transportation field, the data of 36 authoritative SCI journals in the transportation field were collected from the Web of Science core collection database from 2001 to 2020. Based on the bibliometric method, this study used Python to process and visualize data, combined with bibliometric software VOSviewer to assist data visualization. Firstly, a preprocessing data algorithm was designed to deduplicate the collected data, merge synonyms, and extract key technologies. Then the paper records that contained the key technology lexicon were filtered out. Next, the annual number of publications and the distribution of key technologies over time were counted. The least squares method was used to fit the distribution of the annual proportion of the publications, and the slope k1 of the fitted linear regression equation was used to determine the research interest trend of key technologies. The key technologies were divided into “hot technology,” “cold technology,” and “other technologies,” according to the research heat trend. In order to further explore the research hotspots, the least squares method was also used to fit the citations of all technologies to obtain the slope k2. We use the Gaussian mixture model (GMM) algorithm to cluster k1 and k2 of each technology. As a result, the 144 technologies were divided into 13 super-key technologies, 60 key technologies, 59 relative key technologies, and 12 lower-key technologies. Then, the evolution of key technologies was analyzed from two perspectives of weighted evolution and cumulative evolution. And the technology evolution trend in the transportation field in the past 20 years was explored. Finally, the cooccurrence clustering method was adopted to divide key transportation technologies into five categories: vehicle technology and control, optimization algorithms and simulation techniques, artificial intelligence and big data, Internet of Things and computing, and communication technology. The research results can provide references for different people in the transportation field, including but not limited to researchers, journal editors, and funding agencies.

Sign in / Sign up

Export Citation Format

Share Document