The breaking elongation of rotor-spun yarns has been predicted by using linear regression, artificial neural network and neuro-fuzzy models. Cotton fibre properties measured by high volume instrument and yarn count have been used as inputs to the prediction models. Prediction accuracy is found to ...
Finally, we compared the six models by analyzing the similarities of the DNA primary sequences presented in Table 1 and selected the optimal one. 2007 Wiley Periodicals, Inc. J Comput Chem, 2007 展开 关键词: DNA random distribution linear regression model distributions' changes condensed matrices ...
A new model is established by combining the grey model and the linear regression model to synthesize the advantages of the two models, and then the number of oil wear particles in passenger cars is predicted. The three models are used to predict and compare the particle content of different ...
theory model that their prediction accuracy improved 2.46% and 1.35% respectively,and the correlation coefficient of data fitting was also improved.The experimental results showed that the gray linear regression combination prediction model can be used for the better prediction of the mine gas emission...
In THEORY AND APPLICATION OF THE LINEAR MODEL, Franklin A. Graybill integrates the linear statistical model within the context of analysis of variance, correlation and regression, and design of experiments. With topics motivated by real situations, it is a time tested, authoritative resource for ex...
Theory and Application of the Linear Model (Duxbury Classic) 2024 pdf epub mobi 用户评价 评分☆☆☆ 可以当工具书用,第一章复习矩阵(包括g-inverse, c-inverse)。广义线性模型基本都涵盖,不足之处是没有使用Kronecker product来表示Two-way ANOVA。 评分☆☆☆ 可以当工具书用,第一章复习矩阵(包括g-i...
linear regressionleast squaresmembership degreefuzzy weightBecause the conventional linear regression model based on the least squares method is sensitive to abnormal data, the regression equation is less unstable. This paper introduces the concept of the membership degree of the observed data to the ...
5.1 Definition of Linear Regression 5.2 Ordinal Least Square Method 5.3 Assumptions of OLS 5.4 Tests and Intervals 5.5 Multiple Linear Regressionn 5.6 Model Evaluation 5.7 Regression Tutorial 66. Classification Algorithm 6.1.1 Basics of Classification ...
During BPNN testing, an unknown dataset is added to the network to evaluate the efficiency of the trained network. At this stage, the BPNN network is evaluated using linear regression modeling. TheRis determined to analyze the relationship between the BPNN network outputs and the intended output....
nonlinear panel smooth transitional regression modelUnder the new normal, improving capital allocation efficiency is an important way to stimulate economic growth... CL Chen,ZH Zhuang,YT Lin 被引量: 0发表: 2016年 Consumption Credit,Liquidity Constraint and the Consumption of China's Rural Residents:...