Automatic Identification and Optimization Algorithm of Existing Railway Planar Feature Points

2013 ◽  
Vol 779-780 ◽  
pp. 894-898
Author(s):  
Wei Liu ◽  
Hao Pu ◽  
Wei Li ◽  
Hai Feng Zhao
Keyword(s):  
Optimization Algorithm ◽  
Least Square Method ◽  
Least Square ◽  
Automatic Identification ◽  
Engineering Practice ◽  
Feature Points ◽  
Proposed Model ◽  
Acceleration Method ◽  
Planar Feature ◽  
Identification Model

In order to achieve the reconstruction of existing horizontal railway alignments, automatic identification model and optimization algorithm for existing railway planar feature points are proposed. Firstly total least square method of constraint adjustment quantity is proposed, based on which, automatic identification model is built. Then an evaluation function with the radius of circular curve and the lengths of two transition curves as parameters is presented. Based on the direction acceleration method, a reconstruction optimization algorithm is proposed to optimize this ternary implicit function. The proposed model and algorithm can realize the automatic fitting of measuring points and the optimal localization of planar feature points. Example shows that the reconstruction result is considerably superior to the traditional method and is feasible for the engineering practice.

A Skew Detection Algorithm for PDF417 Based on Feature Point

2011 ◽  
Vol 128-129 ◽  
pp. 495-499
Author(s):  
Jian Hua Li ◽  
Ping Li ◽  
Xiao Dan Li ◽  
Yi Wen Wang
Keyword(s):  
Least Square Method ◽  
Detection Algorithm ◽  
Least Square ◽  
Detection Methods ◽  
Automatic Identification ◽  
Feature Points ◽  
Skew Angle ◽  
Bar Code ◽  
Character Code ◽  
The Common

The automatic identification of 2D (two dimensional) bar code PDF417 is very sensitive to skew angle, but, the common skew angle detection methods have shortcomings such as weak performance in time complexity. In this paper, based on the properties of PDF417 character code and the extraction of feature points, we get skew angle of PDF417 bar code image using the least square method. Experiments show that this algorithm has virtue of less computation and high accuracy.

Prediction of Comprehensive Thermal Error of a Preloaded Ball Screw on a Gantry Milling Machine

2017 ◽  
Vol 140 (2) ◽  
Author(s):  
Kuo Liu ◽  
Haibo Liu ◽  
Te Li ◽  
Yongqing Wang ◽  
Mingjia Sun ◽  
...  
Keyword(s):  
Thermal Field ◽  
Thermal Characteristics ◽  
Thermal Error ◽  
Least Square Method ◽  
High Accuracy ◽  
Least Square ◽  
Ball Screw ◽  
Milling Machine ◽  
Thermal Fields ◽  
Proposed Model

The conception of the comprehensive thermal error of servo axes is given. Thermal characteristics of a preloaded ball screw on a gantry milling machine is investigated, and the error and temperature data are obtained. The comprehensive thermal error is divided into two parts: thermal expansion error ((TEE) in the stroke range) and thermal drift error ((TDE) of origin). The thermal mechanism and thermal error variation of preloaded ball screw are expounded. Based on the generation, conduction, and convection theory of heat, the thermal field models of screw caused by friction of screw-nut pairs and bearing blocks are derived. The prediction for TEE is presented based on thermal fields of multiheat sources. Besides, the factors influencing TDE are analyzed, and the model of TDE is established based on the least square method. The predicted thermal field of the screw is analyzed. The simulation and experimental results indicate that high accuracy stability can be obtained using the proposed model. Moreover, high accuracy stability can still be achieved even if the moving state of servo axis changes randomly, the screw is preloaded, and the thermal deformation process is complex. Strong robustness of the model is verified.

Power System Harmonics Estimation using Hybrid Archimedes Optimization Algorithm-based Least Square Method

2021 ◽  
Author(s):  
Hasan Jamil Apon ◽  
Md. Shadman Abid ◽  
Khandaker Adil Morshed ◽  
Mirza Muntasir Nishat ◽  
Fahim Faisal ◽  
...  
Keyword(s):  
Power System ◽  
Optimization Algorithm ◽  
Least Square Method ◽  
Least Square ◽  
Power System Harmonics

System Identification of a Class of Second-Order Continuous System

2014 ◽  
Vol 651-653 ◽  
pp. 528-533 ◽  
Author(s):  
Zhi Gang Jia ◽  
Xing Xuan Wang
Keyword(s):  
Linear Equations ◽  
Continuous System ◽  
Least Square Method ◽  
Second Order ◽  
Least Square ◽  
Step Response ◽  
Order System ◽  
Simulation Results ◽  
Order Continuous ◽  
Identification Model

An identification method of a class of second-order continuous system is proposed. This method constructs a discrete-time identification model, forms a set of linear equations. The parameters can be obtained by least square method. Simulation results show that the method is effective for a class of second-order system, and is not only for step response but also for square wave signal.

Thermal Error Robust Modeling for High-Speed Motorized Spindle

2012 ◽  
Vol 466-467 ◽  
pp. 961-965 ◽  
Author(s):  
Chun Li Lei ◽  
Zhi Yuan Rui ◽  
Jun Liu ◽  
Li Na Ren
Keyword(s):  
High Speed ◽  
Thermal Error ◽  
Least Square Method ◽  
Information Criterion ◽  
Least Square ◽  
Proposed Model ◽  
Nc Machine ◽  
Input Variables ◽  
Thermal Error Model ◽  
Multivariate Autoregressive

To improve the manufacturing accuracy of NC machine tool, the thermal error model based on multivariate autoregressive method for a motorized high speed spindle is developed. The proposed model takes into account influences of the previous temperature rise and thermal deformation (input variables) on the thermal error (output variables). The linear trends of observed series are eliminated by the first difference. The order of multivariate autoregressive (MVAR) model is selected by using Akaike information criterion. The coefficients of the MVAR model are determined by the least square method. The established MVAR model is then used to forecast the thermal error and the experimental results have shown the validity and robustness of this model.

Optimization Study on Leveling Cylinder Position of Telescopic Handler

2011 ◽  
Vol 130-134 ◽  
pp. 2544-2549
Author(s):  
Yong Zhi Lu ◽  
Zhen Xing Su ◽  
Si Jia Wei ◽  
Wang Biao Qiu
Keyword(s):  
Mathematical Model ◽  
Optimization Algorithm ◽  
Least Square Method ◽  
Least Square ◽  
Computer Language ◽  
Master Cylinder ◽  
Multi Objective ◽  
Multi Objective Programming ◽  
Optimization Study ◽  
Accumulated Error

According to research on the leveling principle of the telescopic handler fork, establishing relevant mathematical model to optimize the position of master cylinder with the optimization algorithm of accumulated error, least square method, and multi-objective programming of method of weighting by using the computer language of VB . Then the position of fork got optimization that stabilizes the level of fork of telescopic handler.

scholarly journals Forming a Hierarchical Choquet Integral with a GA-Based Heuristic Least Square Method

Mathematics ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 1155
Author(s):  
Chen ◽  
Huang
Keyword(s):  
Choquet Integral ◽  
Least Square Method ◽  
Least Square ◽  
Integral Model ◽  
Fuzzy Measures ◽  
Proposed Model ◽  
Choquet Integrals ◽  
The Mean ◽  
Input Variables ◽  
Least Mean Squares Algorithm

: Identifying the fuzzy measures of the Choquet integral model is an important component in resolving complicated multi-criteria decision-making (MCDM) problems. Previous papers solved the above problem by using various mathematical programming models and regression-based methods. However, when considering complicated MCDM problems (e.g., 10 criteria), the presence of too many parameters might result in unavailable or inconsistent solutions. While k-additive or p-symmetric measures are provided to reduce the number of fuzzy measures, they cannot prevent the problem of identifying the fuzzy measures in a high-dimension situation. Therefore, Sugeno and his colleagues proposed a hierarchical Choquet integral model to overcome the problem, but it required the partition information of the criteria, which usually cannot be obtained in practice. In this paper, we proposed a GA-based heuristic least mean-squares algorithm (HLMS) to construct the hierarchical Choquet integral and overcame the above problems. The genetic algorithm (GA) was used here to determine the input variables of the sub-Choquet integrals automatically, according to the objective of the mean square error (MSE), and calculated the fuzzy measures with the HLMS. Then, we summed these sub-Choquet integrals into the final Choquet integral for the purpose of regression or classification. In addition, we tested our method with four datasets and compared these results with the conventional Choquet integral, logit model, and neural network. On the basis of the results, the proposed model was competitive with respect to other models.

Complementary Use of Partial Least-Squares and Artificial Neural Networks for the Annual Electricity Consumption Forecast

2012 ◽  
Vol 512-515 ◽  
pp. 1113-1116 ◽  
Author(s):  
Hui Feng Jiang
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Electricity Consumption ◽  
Least Square Method ◽  
Partial Least Square ◽  
Least Square ◽  
Factors Affecting ◽  
The Neural Network ◽  
Proposed Model ◽  
Partial Least Square Method

A model for predicting annual electricity consumption based on the combination of neural network and partial least square method was proposed. The factors affecting the annual electricity consumption are analyzed by means of partial least square method to extract the most important components so that not only the problem of multi-correlation among variables can be solves but also the amount of input dimensions of the neural network can be reduced. Besides, the application of neural network helps to solve the problem of non-linearity of the model. The application example shows that the proposed model has high precision.

Application and Non-Homogeneous Index Grey Model NIGM(1,1,k)

2010 ◽  
Vol 34-35 ◽  
pp. 148-152
Author(s):  
Zhe Ming He ◽  
You Xin Luo ◽  
Bin Zeng
Keyword(s):  
Deductive Reasoning ◽  
Least Square Method ◽  
Least Square ◽  
Grey Model ◽  
Dispersion Index ◽  
Index Function ◽  
Proposed Model ◽  
Modeling Accuracy ◽  
Application Fields ◽  
Formula Computing

To improve the modeling accuracy of grey model and broaden its application fields, a non-homogeneous index grey model (termed NIGM(1,1,k)) was built, which is based on the non-homogeneous dispersion index function and the formula computing the parameters of grey model NIGM(1,1,k) was proposed through the least square method. The function of the time response sequence of the proposed grey model was solved by taking differential equations as a deductive reasoning tool. The proposed grey NIGM(1,1,k) model has the characteristic of high precision as well as high adaptability. Examples validate the practicability and reliability of the proposed model.

scholarly journals Influence of Operating Parameters on Running-in Wear of EN-31 Steel

2016 ◽  
Vol 13 (1) ◽  
pp. 1-2
Author(s):  
M. Hanief ◽  
M. F. Wani
Keyword(s):  
Surface Roughness ◽  
Wear Rate ◽  
Least Square Method ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
Model Parameters ◽  
Operating Parameters ◽  
Proposed Model ◽  
En 31

Abstract In this paper, effect of operating parameters (temperature, surface roughness and load) was investigated to determine the influence of each parameter on the wear rate. A mathematical model was developed to establish a functional relationship between the running-in wear rate and the operating parameters. The proposed model being non-linear, it was linearized by logarithmic transformation and the optimal values of model parameters were obtained by least square method. It was found that the surface roughness has significant effect on wear rate followed by load and temperature. The adequacy of the model was estimated by statistical methods (coefficient of determination (R2) and mean absolute percentage error (MAPE)) .

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