Research on Camera-Oriented Smart Car and Intelligent Control

2012 ◽  
Vol 260-261 ◽  
pp. 342-347
Author(s):  
Zheng Ma ◽  
Guan Bo Wang
Keyword(s):  
Intelligent Control ◽  
Autonomous Navigation ◽  
Least Squares Method ◽  
Least Square Method ◽  
Least Square ◽  
Control Algorithms ◽  
Processing Unit ◽  
Threshold Method ◽  
Central Processing ◽  
Dc Motor Control

This paper designs a camera-oriented smart car along with specialized intelligent control algorithms. MC9S12XS128 is chosen as the central processing unit and a CCD sensor along with peripheral circuit is designed as the camera module. The proposed system integrates technologies of intelligent control, Micro-Electro-Mechanism System (MEMS), System on Chip (SOC), wireless communication and low power consumption embedded technology, realizing autonomous navigation while tracking the path. In the paper, the extraction of path information is streamlined, where dynamic threshold method is used for image binarization and path optimization is done with least square method. Control algorithms are highlighted, where servo control incorporates least squares method creatively and the DC motor control, forming a closed-loop system with a rotatory encoder, adopts incremental PID control algorithm.

Research on Generator Excitation Parameter Identification - PSS Low-Pass Link Parameter Identification

2013 ◽  
Vol 805-806 ◽  
pp. 716-720
Author(s):  
Tao Xu ◽  
Tian Long Shao ◽  
Dong Fang Zhang
Keyword(s):  
Mathematical Model ◽  
Parameter Identification ◽  
Least Squares Method ◽  
Least Square Method ◽  
Least Square ◽  
National Standards ◽  
Matlab Software ◽  
Low Pass ◽  
Newton Iterations ◽  
The Mathematical Model

Combined with the contents of the study-PSS low-pass link parameter identification. Least-squares method is selected. Using least-square method for PSS low-pass link mathematical model are also deduced. For the results, because of the mathematical model is solving nonlinear equations, cannot used by the Newton method directly. So we choose to use Newton iterations, with this feature, choose to use MATLAB software to solve the equation. Identification of the use of MATLAB software lags after the PSS parameters obtained recognition results compared with national standards, identifying and verifying the practicability.

Fuzzy C-Regression Models

2013 ◽  
Vol 278-280 ◽  
pp. 1323-1326
Author(s):  
Yan Hua Yu ◽  
Li Xia Song ◽  
Kun Lun Zhang
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Linear Models ◽  
Least Squares Method ◽  
Least Square Method ◽  
Least Square ◽  
Estimation Methods ◽  
Statistical Regression ◽  
Fuzzy Linear Regression ◽  
Fuzzy Degree

Fuzzy linear regression has been extensively studied since its inception symbolized by the work of Tanaka et al. in 1982. As one of the main estimation methods, fuzzy least squares approach is appealing because it corresponds, to some extent, to the well known statistical regression analysis. In this article, a restricted least squares method is proposed to fit fuzzy linear models with crisp inputs and symmetric fuzzy output. The paper puts forward a kind of fuzzy linear regression model based on structured element, This model has precise input data and fuzzy output data, Gives the regression coefficient and the fuzzy degree function determination method by using the least square method, studies the imitation degree question between the observed value and the forecast value.

scholarly journals The Relationship between Environmental Information Disclosure and Profitability: A Comparison between Different Disclosure Styles

2019 ◽  
Vol 16 (9) ◽  
pp. 1556 ◽  
Author(s):  
Hua Yin ◽  
Mingyu Li ◽  
Yuan Ma ◽  
Qiang Zhang
Keyword(s):  
Information Disclosure ◽  
Least Squares Method ◽  
Least Square Method ◽  
Environmental Information ◽  
Least Square ◽  
Policy Implications ◽  
Corporate Managers ◽  
Environmental Information Disclosure ◽  
Research Gap ◽  
The Relationship

Combined with the existing research gap, this paper divides firms’ environmental information disclosure styles into two types: Substantive style and symbolic style. This paper elaborates on the relationship between environmental information disclosure and firms’ profitability of these two disclosure types and tests this relationship using the data from 676 firms employed from the heave-polluting industry. Considering the endogenous and heteroscedasticity problems, 2-stage least squares method and weighted least square method were adopted. The results showed that (1) positive relationships exist between environmental information disclosure and profitability for both types; and (2) the contribution of symbolic-style disclosure to profitability is larger than that of substantive-style disclosure. These findings are important for corporate managers and highlight some policy implications in developing countries.

Solitary waves of the RLW equation via least squares method

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ozlem Ersoy Hepson ◽  
Idris Dag ◽  
Bülent Saka ◽  
Buket Ay
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Least Square Method ◽  
Least Square ◽  
Spline Functions ◽  
Algebraic Equations ◽  
B Spline ◽  
B Splines ◽  
Rlw Equation ◽  
Set Up

Abstract Integration using least squares method in space and Crank–Nicolson approach in time is managed to set up an algorithm to solve the RLW equation numerically. Trial functions in the least square method consist of a combination of the quartic B-spline functions. Integration of the RLW equation gives a system of algebraic equations. The solutions consisting of a combination of the quartic B-splines are given for some initial and boundary value problems of RLW equation.

A New Method to Identify the Preisach Distribution Function of Hysteresis

2005 ◽  
Vol 475-479 ◽  
pp. 2107-2110 ◽  
Author(s):  
Fan Li ◽  
Jian Qin Mao ◽  
Hai Shan Ding ◽  
Wen Bo Zhang ◽  
Hui Bin Xu ◽  
...  
Keyword(s):  
Distribution Function ◽  
Least Squares ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Least Squares Method ◽  
Input Sequence ◽  
Least Square Method ◽  
Least Square ◽  
New Method ◽  
Inference System

In this paper, a new method which combines the least square method with Tree-Structured fuzzy inference system is presented to approximate the Preisach distribution function. Firstly, by devising the input sequence and measure the output, discrete Preisach measure can be identified by the use of the least squares method. Then, the Preisach function can be obtained with Tree-Structured fuzzy inference system without any special smoothing means. So, this new method is not sensitive to noise, and is a universal approximator of the Preisach function. It collect the merit and overcome the deficiency of the existing methods.

Research on the Least Squares Method in Error Compensation on RSSI Ranging

2011 ◽  
Vol 340 ◽  
pp. 121-125
Author(s):  
Wei Xin Ling ◽  
Jing Min Gao ◽  
Chun Yun Li
Keyword(s):  
Wireless Communications ◽  
Error Compensation ◽  
Least Squares Method ◽  
Data Use ◽  
Least Square Method ◽  
Least Square ◽  
Gaussian Filter ◽  
Communications Networks ◽  
Improving Accuracy ◽  
After Error

This paper describes error compensation using least square method in wireless communications networks. The received data use the Gaussian filter to avoid interference，then use least square to compensate the error. ZigBee sensor network is constructed to verify the proposed algorithm. The experiment has been taken to test the accuracy after error compensation. The result shows the method is available for improving accuracy.

scholarly journals Time Scale in Least Square Method

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Özgür Yeniay ◽  
Öznur İşçi ◽  
Atilla Göktaş ◽  
M. Niyazi Çankaya
Keyword(s):  
Least Squares ◽  
Time Scale ◽  
Least Squares Method ◽  
Least Square Method ◽  
Forward Direction ◽  
Ordinary Least Squares ◽  
Least Square ◽  
Regression Equations ◽  
Nabla Derivative ◽  
Derivative Concept

Study of dynamic equations in time scale is a new area in mathematics. Time scale tries to build a bridge between real numbers and integers. Two derivatives in time scale have been introduced and called as delta and nabla derivative. Delta derivative concept is defined as forward direction, and nabla derivative concept is defined as backward direction. Within the scope of this study, we consider the method of obtaining parameters of regression equation of integer values through time scale. Therefore, we implemented least squares method according to derivative definition of time scale and obtained coefficients related to the model. Here, there exist two coefficients originating from forward and backward jump operators relevant to the same model, which are different from each other. Occurrence of such a situation is equal to total number of values of vertical deviation between regression equations and observation values of forward and backward jump operators divided by two. We also estimated coefficients for the model using ordinary least squares method. As a result, we made an introduction to least squares method on time scale. We think that time scale theory would be a new vision in least square especially when assumptions of linear regression are violated.

Research on Boundary Extraction of STL Models based on Genetic Algorithm

2012 ◽  
Vol 566 ◽  
pp. 78-81
Author(s):  
Jing Bin Hao ◽  
Zhong Bin Wang ◽  
Hai Feng Yang ◽  
Zhong Kai Li
Keyword(s):  
Genetic Algorithm ◽  
Extraction Method ◽  
Least Square Method ◽  
Least Square ◽  
Threshold Method ◽  
Boundary Extraction ◽  
Large Complex ◽  
Complex Models ◽  
Curvature Information ◽  
Best Fit

To efficiently decompose a large complex STL model, an improved boundary extraction method is proposed based on genetic algorithm. Three curvature parameters (dihedral angle, perimeter ration and convexity) were used to estimate the surface curvature information. Genetic Algorithm (GA) is used to determinate the threshold of feature edge. The discrete feature edges are grouped and filtered using the best-fit plane (BFP), which is calculated by Least Square Method (LSM). Several experimental results demonstrate that the amount of feature edges is about half of the preset threshold method, and useful feature edges were reserved. The extracted feature boundaries can be directly used to decompose large complex models.

Methods of Feature Weighting Calculation and Case Retrieval in CBR Case Base

2014 ◽  
Vol 490-491 ◽  
pp. 1391-1398
Author(s):  
Xiao Ping Li
Keyword(s):  
Least Squares Method ◽  
Least Square Method ◽  
High Accuracy ◽  
Typical Case ◽  
Feature Weighting ◽  
Least Square ◽  
Case Retrieval ◽  
Use Of Data ◽  
On Line ◽  
Simulation Results

This article proposes the necessity and feasibility of the use of Data Mining and Knowledge Discovery in CBR reasoning. This paper focuses on the method of empowering feature items based on least squares method parameter identification, and achieve the method of Similarity case retrieval on this basis, the object is the typical case database of railway rescue. The simulation results show that: the least square method can effectively make estimation and identification of the feature parameters, and can continuously correct on-line. High accuracy and fast convergence characteristics of the assigned parameters show that the algorithm has a certain application value.

scholarly journals A Study of Climate Data Using Least Square Method and the Fast Fourier Transform

2009 ◽  
Vol 6 (2) ◽  
pp. 31
Author(s):  
Masriah Awang ◽  
Zainazlan Md Zain ◽  
Nur Sa’aidah Ismail
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Least Squares Method ◽  
Least Square Method ◽  
Least Square ◽  
Energy Utilization ◽  
Climatic Data ◽  
Climate Data ◽  
Optimum Energy ◽  
External Conditions

Energy utilization in buildings continues to increase as the quality of life increases. Buildings are built in an environment in which the climate surrounding a building is a factor influencing the energy requirements for the building services. The higher the thermal stress due to external conditions, the higher the energy required to provide consistent building services. This paper discusses the different types of climate analyses for Subang. The climate data has been calculated using averaged hourly values per month. The least squares method and fast Fourier transform have been used to explore the data further and elucidate climatic data. The climatic data collected and presented include temperature distribution, solar radiation, relative humidity distribution, rainfall distribution, wind-speed distribution and pressure distribution were presented. The least square polynomial of degree four and ten were chosen to represent the climate data. The least square error and the norm of the residual for these two polynomials were the smallest obtained amongst the other polynomials. The coefficients of determination were also calculated. The Fast Fourier Transform (FFT) from the MATLAB toolbox was used to evaluate patterns within the climate data. The FFT shows the Fourier coefficient on the complex plane. These studies reveal the climate patterns that need to be considered for optimum energy utilization in buildings. 

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