scholarly journals Application of PCA Analysis and QR Decomposition to Address RFM's Ill-Posedness

2020 ◽  
Vol 86 (1) ◽  
pp. 17-21 ◽  
Author(s):  
Amin Alizadeh Naeini ◽  
Sayyed Hamed Alizadeh Moghaddam ◽  
Mohammad Moein Sheikholeslami ◽  
AliReza Amiri-Simkooei
Keyword(s):  
Control Point ◽  
Principal Component ◽  
Least Square Method ◽  
Qr Decomposition ◽  
Least Square ◽  
Design Matrix ◽  
Step Method ◽  
Small Perturbations ◽  
Sensor Model ◽  
Highly Correlated

Rational function model (<small>RFM</small>) is the most widely used sensor model in the remote sensing community. However, it suffers from ill-posedness, challenging its feasibility. This problem, i.e., ill-posedness, is mainly caused due to highly correlated coefficients of the <small>RFM</small>, which magnifies any small perturbations of observations, such as noise and instrumental error. This paper outlines a novel two-step method, called principal component analysis (<small>PCA</small>)-<small>RFM</small>, based on the integration of <small>PCA</small> and QR decomposition. In the first step, the <small>PCA</small>-<small>RFM</small> reduces the observational perturbations from the design matrix using the <small>PCA</small>. In the next step, the <small>RFM</small>'s coefficients are estimated using a <small>QR</small> decomposition with column pivoting and least square method. According to the results, the <small>PCA</small>-<small>RFM</small> is less sensitive than its rivals to the changes of the ground control point (<small>GCPs</small>) distribution. Geometrically speaking, in addition, <small>PCA</small>-<small>RFM</small> is more accurate than recently established methods even in the presence of the small number of <small>GCPs</small>.

scholarly journals Statistical Modelling of Intensity Modes of Rainfall Using Principal Component Itemization: A Case Study of Kano State

2020 ◽  
pp. 46-56
Author(s):  
Ibrahim Abubakar Sadiq ◽  
Nazir Muhammad Isah
Keyword(s):  
Hidden Variables ◽  
Principal Component ◽  
Least Square Method ◽  
Statistical Modelling ◽  
Least Square ◽  
Moderate Intensity ◽  
Weather Extremes ◽  
Economic Sectors ◽  
Study Region ◽  
Changing Patterns

Kano State is experiencing greater weather extremes, changes in rainfall patterns, analysis of heat and cold waves, and increasing droughts and floods (Kano meteorological agency). As a result, there is a need for the provision of the necessary weather advisories and early warnings to planners, decision-makers, and operators of the various rainfall-sensitive socio-economic sectors. However, this study is aiming to realize some hidden variables of Kano State total monthly rainfall dataset from the onset to cessation period of rain from the month of April to October over a 105 years (1911-2015) for classification into the intensity of the rain of the area under study, also to determine the linear model for the changing patterns of rainfall in Kano State and to identify some of the adverse impacts on socio-economic sectors and transport infrastructures. Thus, the appearances of the rainfall figure are established for the study region with the operation of Principal Component Analysis (PCA), application least square method. The leading three (3) PCs, gives account for about 61% of the entire disparity, is described. The revision displays and describe PC1 as associated with the heavy intensity rainfall, whereas PC2 is connected to the moderate-intensity rainfall and finally PC3 is linked to the light intensity rainfall of the region under study. By the scores of our PCs, uniform rainfall zones are established over the region of enquiring to which the yearly performance of rainfall is discussed. Statistically, all three models for the various mode of rainfall intensity are significant, which serves as the annual pattern of rainfall in the study area.

scholarly journals ANALISIS REGRESI KOMPONEN UTAMA UNTUK MENGATASI MASALAH MULTIKOLINIERITAS DALAM ANALISIS REGRESI LINIER BERGANDA

2012 ◽  
Vol 6 (1) ◽  
pp. 31-40
Author(s):  
Gresyea L. Marcus ◽  
Henry J. Wattimanela ◽  
Yopi A. Lesnussa
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Least Square Method ◽  
Component Analysis ◽  
Least Square ◽  
Ordinary Least Square ◽  
Independent Variables ◽  
Analysis Technique ◽  
Independent Variable ◽  
Very High

The climate in Ambon, are influenced by sea climate and season climate, cause of this island arrounded by sea, it is make very high rainfall intensity. A very high collinearity between independent variables, make the estimate can not rely be ordinary least square method so it market with not real regretion coefficient and the collinearity. Collinearity can be detected by linier correlation coefficient between independent variables and also with VIF way. Regretion principal component analysis is used to remove collinearity and all of independent variable into model, this analysis is regretion analysis technique wher eare combinated with principal component analysis technique. The object of this analysis is to simplify the variable by overcast it dimension, we can do it removes the correlation between coefficient by transformation. Regresion can help to solve this case rainfall in Ambon on 2010. So the colinearity to independent variables can be overcome and then we can get the best regretion rutes.

Study on Two-Step Method for Robot Dynamics Parameters Calibration

2012 ◽  
Vol 605-607 ◽  
pp. 1557-1562 ◽  
Author(s):  
Qing Xuan Jia ◽  
Tong Li ◽  
Gang Chen
Keyword(s):  
Inverse Method ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Second Step ◽  
Robot Dynamics ◽  
Joint Movement ◽  
Step Method ◽  
Multidimensional Matrix ◽  
Pseudo Inverse

In order to obtain accurate dynamics parameters, a two-step method for robot dynamics parameters calibration is presented. In the first step a multidimensional matrix is constituted through transforming the configurations of robot manipulators and the product of quality and centroid coordinate about links is solved by using the least square method. In the second step decoupling dynamic equation of robot is deduced based on Newton-Euler algorithm, and through planning specific joint movement, the inertia tensor and centroid coordinate of robot links are calibrated making use of the pseudo inverse method. By the above two steps, the entire calibration of robot dynamic parameters is achieved. The correctness and feasibility of the presented calibration method is manifested by simulations and experiments.

The Development and Assessment of a New CHF Correlation for PWR Fuel Assemblies

2013 ◽  
Author(s):  
Ning Bai ◽  
Wei Liu ◽  
Yuanbing Zhu ◽  
Jianqiang Shan ◽  
Bo Zhang ◽  
...  
Keyword(s):  
Least Square Method ◽  
Least Square ◽  
Uniform Heat Flux ◽  
Analysis Method ◽  
Step Method ◽  
Local Flow ◽  
Spacer Grids ◽  
Fuel Assemblies ◽  
High Prediction ◽  
Cold Walls

The CHF in PWR fuel assemblies is usually predicted by the local flow correlation approach based on subchannel analysis while the effects of spacer grids, cold walls, non-uniform heat flux, etc are investigated. By using the subchannel code ATHAS to calculate each set of bundle CHF data, the local thermal-hydraulic parameters at DNB occurrence point were obtained. In present study, the minimum DNBR point method was applied to develop a new CHF correlation for PWR fuel assemblies. The so-called “three-step method” and “magnitude analysis method” were used to determine the shape and the expression of each item, respectively and the least square method was applied to determine the coefficients of the correlation. Based on the large database of CHF tests, the CHF correlation named ACC correlation has been developed to calculate the risk of DNB. The analysis and assessment results indicate that the ACC correlation can fit the experimental data well with high prediction accuracy and correct parametric trends. Coupled with subchannel code ATHAS, this correlation can simulate the thermal-hydraulics performances of PWR fuel assemblies exactly.

Application of Coordinate Conversion in the Tunnel through

2012 ◽  
Vol 204-208 ◽  
pp. 2792-2795
Author(s):  
Xiu Dong Qi ◽  
Zhong Yi Wang
Keyword(s):  
Hong Kong ◽  
Coordinate Transformation ◽  
Control Point ◽  
Least Square Method ◽  
Least Square ◽  
Coordinate Systems ◽  
Technical Issue ◽  
Public Control ◽  
Projection Length ◽  
Coordinate Conversion

The transformation between different coordinate systems is a technical issue in the process of surveying and mapping. Guangzhou-Shenzhen-Hong Kong Passenger ZH-4 contract Huanggang tunnel passes Shenzhen and Hong Kong. Its coordinates belong to different coordinate systems. In order to ensure the tunnel through quality, coordinate conversion accuracy perpendicular to the direction of tunnel axis should be main consideration when coordinate transformation. According to the characteristics of the tunnel project, using four-parameter model and the least square method. Through composing different public control point, and comparing the tunnel through the point and the cut-off point the projection length of conversion residuals on the important through direction, the optimal transformation parameters have been selected.

Direct Assessment of Effective Renal Plasma Flow from Renoscintigraphy with a Gamma Camera and an On-Line Computer

1981 ◽  
Vol 20 (06) ◽  
pp. 274-278
Author(s):  
J. Liniecki ◽  
J. Bialobrzeski ◽  
Ewa Mlodkowska ◽  
M. J. Surma
Keyword(s):  
Count Rate ◽  
Renal Plasma Flow ◽  
Early Period ◽  
Least Square Method ◽  
Least Square ◽  
Uptake Coefficient ◽  
Positive Linear Correlation ◽  
On Line ◽  
Best Fit ◽  
Plasma Activity

A concept of a kidney uptake coefficient (UC) of 131I-o-hippurate was developed by analogy from the corresponding kidney clearance of blood plasma in the early period after injection of the hippurate. The UC for each kidney was defined as the count-rate over its ROI at a time shorter than the peak in the renoscintigraphic curve divided by the integral of the count-rate curve over the "blood"-ROI. A procedure for normalization of both curves against each other was also developed. The total kidney clearance of the hippurate was determined from the function of plasma activity concentration vs. time after a single injection; the determinations were made at 5, 10, 15, 20, 30, 45, 60, 75 and 90 min after intravenous administration of 131I-o-hippurate and the best-fit curve was obtained by means of the least-square method. When the UC was related to the absolute value of the clearance a positive linear correlation was found (r = 0.922, ρ > 0.99). Using this regression equation the clearance could be estimated in reverse from the uptake coefficient calculated solely on the basis of the renoscintigraphic curves without blood sampling. The errors of the estimate are compatible with the requirement of a fast appraisal of renal function for purposes of clinical diagknosis.

PENGARUH KNOWLEDGE MANAGEMENT, KOMPETENSI, MOTIVASI TERHADAP KINERJA KARYAWAN

2015 ◽  
Vol 5 (2) ◽  
pp. 1
Author(s):  
Miftahol Arifin
Keyword(s):  
Knowledge Management ◽  
Linear Regression ◽  
Significant Influence ◽  
Employee Performance ◽  
Least Square Method ◽  
Least Square ◽  
Analysis Tool ◽  
Ordinary Least Square ◽  
Competence Motivation ◽  
Performance Analyze

The purpose of this research is to analyze the influence of knowledge management on employee performance, analyze the effect of competence on employee performance, analyze the influence of motivation on employee performance). In this study, samples taken are structural employees PT.centris Kingdom Taxi Yogyakarta. The analysis tool in this study using multiple linear regression with Ordinary Least Square method (OLS). The conclusion of this study showed that the variables of knowledge management has a significant influence on employee performance, competence variables have an influence on employee performance, motivation variables have an influence on employee performance, The analysis showed that the variables of knowledge management, competence, motivation on employee performance.Keywords: knowledge management, competence, motivation, employee performance.

Pemanfaatan CFSRv2 untuk Statistical Downscaling menggunakan Principal Component Regression dan Partial Least Square

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Khairunnisa Khairunnisa ◽  
Rizka Pitri ◽  
Victor P Butar-Butar ◽  
Agus M Soleh
Keyword(s):  
Statistical Downscaling ◽  
General Circulation ◽  
Principal Component Regression ◽  
Circulation Model ◽  
Principal Component ◽  
Meteorological Station ◽  
Grid Size ◽  
Partial Least Square ◽  
Least Square ◽  
Output Data

This research used CFSRv2 data as output data general circulation model. CFSRv2 involves some variables data with high correlation, so in this research is using principal component regression (PCR) and partial least square (PLS) to solve the multicollinearity occurring in CFSRv2 data. This research aims to determine the best model between PCR and PLS to estimate rainfall at Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station by comparing RMSEP value and correlation value. Size used was 3×3, 4×4, 5×5, 6×6, 7×7, 8×8, 9×9, and 11×11 that was located between (-40) N - (-90) S and 1050 E -1100 E with a grid size of 0.5×0.5 The PLS model was the best model used in stastistical downscaling in this research than PCR model because of the PLS model obtained the lower RMSEP value and the higher correlation value. The best domain and RMSEP value for Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station is 9 × 9 with 100.06, 6 × 6 with 194.3, 8 × 8 with 117.6, and 6 × 6 with 108.2, respectively.

Sign in / Sign up

Export Citation Format

Share Document