Study on Identification and Classification of Expansive Soil Based on Bayes Discriminant Analysis Method

2013 ◽  
Vol 639-640 ◽  
pp. 573-576
Author(s):  
Yan Jun Qiu ◽  
Chang Ping Wen
Keyword(s):  
Discriminant Analysis ◽  
Expansive Soil ◽  
Liquid Limit ◽  
Analysis Method ◽  
Discriminant Model ◽  
Normal Populations ◽  
Proposed Model ◽  
Practical Engineering ◽  
Bayes Discriminant Analysis

Based on the principle of Bayes discriminant analysis, Bayes discriminant model (BDM) for evaluation of expansive soil in sub-grades is established. Four indexes including free expansive ratio, liquid limit, plasticity index and moisture content of standard absorption are selected as the factors for synthetic evaluation of expansive soil. The grade of shrink and expansion is divided into four grades that are regarded as four normal populations in Bayes discriminant analysis. Bayes discriminant functions obtained through training a set of expansive soil samples are employed to compute the Bayes function values of the evaluating samples, and the maximal function value is used to judge which population the evaluating sample belongs to. The optimality of the proposed model is verified by back-substitution method. The study shows that the prediction accuracy of the proposed model is 100% and could be used in practical engineering.

Assessment of Urban Road Traffic Safety Based on Bayes Discriminant Analysis Method

2013 ◽  
Vol 639-640 ◽  
pp. 544-547
Author(s):  
Chang Ping Wen ◽  
Qing Qing Tian
Keyword(s):  
Discriminant Analysis ◽  
Traffic Safety ◽  
Evaluation Method ◽  
Road Traffic ◽  
Urban Road ◽  
Discriminant Model ◽  
Road Traffic Safety ◽  
Normal Populations ◽  
Proposed Model ◽  
Bayes Discriminant Analysis

Bayes discriminant analysis theory (BDAT) is used to create an evaluation method to determine the condition of urban road traffic safety. The resulting Bayes discriminant model (BDM) is designed to strictly adhere to BDAT. Three indexes including death ratio per ten thousand vehicles, death ratio per hundred thousand bicycles and death ratio per hundred thousand citizens are selected as the factors in the analysis of urban road traffic safety. The grade of condition of urban road traffic safety is divided into three grades that are regarded as three normal populations in Bayes discriminant analysis. Bayes discriminant functions rigorously constructed through training a set of samples are employed to compute the Bayes function values of the evaluating samples, and the maximal function value is used to judge which population the evaluating sample belongs to. The optimality of the proposed model is verified by back-substitution method. The study shows that the prediction accuracy of the proposed model is 100% and could be used in practice.

Methods of Support Vector Machine on Classification of Expansive Soils

2012 ◽  
Vol 531 ◽  
pp. 562-565 ◽  
Author(s):  
Hai Ying Yang ◽  
Yun Liu
Keyword(s):  
Support Vector Machine ◽  
Expansive Soils ◽  
Expansive Soil ◽  
Liquid Limit ◽  
Classification Model ◽  
Support Vector ◽  
Large Set ◽  
Practical Engineering ◽  
Machine Analysis

The classification of the grade of shrink and expansion for the expansive soils was the initial and essential work for engineering construction in expansive soil area. Based on the principle of support vector machine analysis, a classification model of expansive was established in this paper, including five indexes reflecting the shrink and expansion of expansive soil, liquid limit, swell-shrink total ratio, plasticity index, water contents and free expansive ratio and functions were obtained through training a large set of expansive samples. It was shown that the classification model of SVM analysis is an effective method performed excellently with high prediction accuracy and could be used in practical engineering.

scholarly journals The use of discriminant analysis methods for diagnosis of the causes of differences in the properties of resin mortar containing various fillers

2018 ◽  
Vol 49 ◽  
pp. 00017 ◽  
Author(s):  
Bernardeta Dębska
Keyword(s):  
Discriminant Analysis ◽  
Model Building ◽  
Analysis Method ◽  
Learning Stage ◽  
Independent Variables ◽  
Prognostic Accuracy ◽  
Wide Range ◽  
Exploratory Data ◽  
Prediction Problems

Resin mortars belong to the group of concrete-like construction composites. They are obtained by mixing a synthetic resin with a hardener and an appropriately selected aggregate. The latter component is usually as much as 90% of the composite mass and can largely shape the characteristics of the finished product. The fact that the type of filler used can significantly differentiate the values of physical and mechanical parameters of epoxy mortars is confirmed by the results of the exploratory data analysis method used in this article, which is discriminant analysis. This allows us to examine differences between groups of objects based on a set of selected independent variables (predictors). It is used to solve a wide range of classification and prediction problems. The core of discriminant analysis is a model presented in the form of a linear combination of independent variables, which allows classification of observations (e.g. test mortars) into one of the groups that are of interest to the researcher. In discriminant analysis one can distinguish the learning stage (model building), in which classification rules are created based on research results (training set) and the classification stage, i.e. the use of the model, e.g. for testing its prognostic accuracy.

scholarly journals Discrimination and Classification of Poultry Feeds Data

2013 ◽  
Vol 2 (5) ◽  
pp. 37-44
Author(s):  
Olosunde A.A ◽  
Soyinka A.T
Keyword(s):  
Statistical Analysis ◽  
Discriminant Analysis ◽  
Discriminant Function ◽  
Copper Salt ◽  
Analysis Method ◽  
Linear Discriminant ◽  
Discriminant Analysis Method ◽  
Organic Copper ◽  
Fisher’S Linear Discriminant

This study is aimed at employing discriminant analysis method and classification for the purpose of achieving the assessment of a discriminant function through which we can discover the reasons of the actual difference between two groups of eggs of which the chicken were fed with different combination of feeds. Fisher’s Linear Discriminant Function (LDA) was used as a tool for the Statistical analysis. It was estimated on the basis of a sample of 96 chickens, which were classified into two groups of 48 chickens each. One group was fed with in-organic copper salt combination while the second group with organic copper salt combination. Some important attributes are measured from the eggs produced from these two groups; such as egg’s size(g) and cholesterol level(mg).The results obtained assert the efficiency of the discriminant function which we obtained and the possibility of its use for the purpose of discriminating and classifying the eggs of unknown feeds into corresponding group in future.

Classification of Chinese tea leaves using laser-induced breakdown spectroscopy combined with the discriminant analysis method

2016 ◽  
Vol 8 (15) ◽  
pp. 3204-3209 ◽  
Author(s):  
Jinmei Wang ◽  
Peichao Zheng ◽  
Hongdi Liu ◽  
Liang Fang
Keyword(s):  
Discriminant Analysis ◽  
Green Tea ◽  
Black Tea ◽  
Laser Induced Breakdown Spectroscopy ◽  
Analysis Method ◽  
Tea Leaves ◽  
Breakdown Spectroscopy ◽  
Discriminant Analysis Method ◽  
Laser Induced Breakdown

Six types of tea leaves, including Longjing green tea, Mengding Huangya, white tea, Tie Guanyin, Wuyi black tea and Pu'er tea, were analyzed and identified using laser-induced breakdown spectroscopy (LIBS) combined with the discriminant analysis (DA) method.

Bayesian Discriminant Analysis of Yogurt Products Based on Raman Spectroscopy

2020 ◽  
Vol 103 (5) ◽  
pp. 1435-1439 ◽  
Author(s):  
Zheng-Yong Zhang ◽  
An-Yang Yao ◽  
Tong-Tong Yue ◽  
Min-Qiu Niu ◽  
Hai-Yan Wang
Keyword(s):  
Raman Spectroscopy ◽  
Discriminant Analysis ◽  
Posterior Probability ◽  
Dairy Product ◽  
Principal Component ◽  
Mean Values ◽  
Discriminant Model ◽  
Important Basis ◽  
Component Feature

Abstract Background The quality discrimination of dairy products is an important basis on which to achieve quality assurance. Objective Taking the discriminant analysis of brand yogurt products as an example, a new rapid discriminant method can be constructed. Method The first three principal components were selected as the pattern vectors of the samples. Then, at random, 75% of the samples were collected as a training set, and their mean values and covariance matrices were calculated to construct a Gauss Bayesian discriminant model. The remaining 25% of samples were employed as a test set, and the pattern vectors of each sample were input into the above model. Next, the posterior probability of each sample in relation to each category could be obtained. Results: The category corresponding to the maximum posterior probability as the brand classification of each sample was defined. Conclusions We constructed a Gauss Bayesian discriminant model to discriminate these different yogurt products after the principal component feature extraction of Raman properties. The results indicate the rationality and wide application prospects of this approach. Highlights A fast dairy product discriminant method based on Gauss Bayesian model and Raman spectroscopy was established.

scholarly journals Statistical Analyses of Femur Parameters for Designing Anatomical Plates

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Lin Wang ◽  
Kunjin He ◽  
Zhengming Chen
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Individual Differences ◽  
Discriminant Analysis ◽  
Statistical Methods ◽  
Proper Class ◽  
The Mean ◽  
Parameter Values ◽  
Bayes Discriminant Analysis

Femur parameters are key prerequisites for scientifically designing anatomical plates. Meanwhile, individual differences in femurs present a challenge to design well-fitting anatomical plates. Therefore, to design anatomical plates more scientifically, analyses of femur parameters with statistical methods were performed in this study. The specific steps were as follows. First, taking eight anatomical femur parameters as variables, 100 femur samples were classified into three classes with factor analysis and Q-type cluster analysis. Second, based on the mean parameter values of the three classes of femurs, three sizes of average anatomical plates corresponding to the three classes of femurs were designed. Finally, based on Bayes discriminant analysis, a new femur could be assigned to the proper class. Thereafter, the average anatomical plate suitable for that new femur was selected from the three available sizes of plates. Experimental results showed that the classification of femurs was quite reasonable based on the anatomical aspects of the femurs. For instance, three sizes of condylar buttress plates were designed. Meanwhile, 20 new femurs are judged to which classes the femurs belong. Thereafter, suitable condylar buttress plates were determined and selected.

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