This research proposes a measure called cluster similar index(CSI)to evaluate the similarity of cluster for discrete elements.The CSI is used as a criterion to build the automatic fuzzy clustering algorithm.This algor...This research proposes a measure called cluster similar index(CSI)to evaluate the similarity of cluster for discrete elements.The CSI is used as a criterion to build the automatic fuzzy clustering algorithm.This algorithm can determine the suitable number of clusters,find the elements in each cluster,give the probability to belong to the clusters of each element,and evaluate the quality of the established clusters at the same time.The proposed algorithm can perform quickly and effectively by the established MATLAB procedure.Several numerical examples illustrate the proposed algorithm and show the advantages in comparing with the existing ones.Finally,applying the proposed algorithm in the image recognition shows potentiality in the reality of this research.展开更多
This article proposes some related issues to classification problem by Bayesian method for two populations.They are relationships between Bayes error(BE)and other measures and the results for determining the BE.In add...This article proposes some related issues to classification problem by Bayesian method for two populations.They are relationships between Bayes error(BE)and other measures and the results for determining the BE.In addition,we propose three methods to find the prior probabilities that can make to reduce BE.The calculation of these methods can be performed conveniently and efficiently by the MATLAB procedures.The new approaches are tested by the numerical examples including synthetic and benchmark data and applied in medicine and economics.These examples also show the advantages of the proposed methods in comparison with existing methods.展开更多
Based on the improvement in establishing the relations of data,this study proposes a new fuzzy time series model.In this model,the suitable number of fuzzy sets and their specific elements are determined automatically...Based on the improvement in establishing the relations of data,this study proposes a new fuzzy time series model.In this model,the suitable number of fuzzy sets and their specific elements are determined automatically.In addition,using the percentage variations of series between consecutive periods of time,we build the fuzzy function.Incorporating all these improvements,we have a new fuzzy time series model that is better than many existing ones through the well-known data sets.The calculation of the proposed model can be performed conveniently and efficiently by a MATLAB procedure.The proposed model is also used in forecasting for an urgent problem in Vietnam.This application also shows the advantages of the proposed model and illustrates its effectiveness in practical application.展开更多
This study proposes some results in classifying by Bayesian method. There are upper and lowerbounds of the Bayes error as well as its determination in case of one dimension and multidimensions. Based on the proposals ...This study proposes some results in classifying by Bayesian method. There are upper and lowerbounds of the Bayes error as well as its determination in case of one dimension and multidimensions. Based on the proposals for estimating of probability density functions, calculatingthe Bayes error and determining the prior probability, we establish an algorithm to evaluateability of customers to pay debts at banks. This algorithm has been performed by the Matlabprocedure that can be applied well with real data. The proposed algorithm is tested by the realapplication at a bank in Viet Nam that obtains the best results in comparing with the existingapproaches.展开更多
文摘This research proposes a measure called cluster similar index(CSI)to evaluate the similarity of cluster for discrete elements.The CSI is used as a criterion to build the automatic fuzzy clustering algorithm.This algorithm can determine the suitable number of clusters,find the elements in each cluster,give the probability to belong to the clusters of each element,and evaluate the quality of the established clusters at the same time.The proposed algorithm can perform quickly and effectively by the established MATLAB procedure.Several numerical examples illustrate the proposed algorithm and show the advantages in comparing with the existing ones.Finally,applying the proposed algorithm in the image recognition shows potentiality in the reality of this research.
文摘This article proposes some related issues to classification problem by Bayesian method for two populations.They are relationships between Bayes error(BE)and other measures and the results for determining the BE.In addition,we propose three methods to find the prior probabilities that can make to reduce BE.The calculation of these methods can be performed conveniently and efficiently by the MATLAB procedures.The new approaches are tested by the numerical examples including synthetic and benchmark data and applied in medicine and economics.These examples also show the advantages of the proposed methods in comparison with existing methods.
文摘Based on the improvement in establishing the relations of data,this study proposes a new fuzzy time series model.In this model,the suitable number of fuzzy sets and their specific elements are determined automatically.In addition,using the percentage variations of series between consecutive periods of time,we build the fuzzy function.Incorporating all these improvements,we have a new fuzzy time series model that is better than many existing ones through the well-known data sets.The calculation of the proposed model can be performed conveniently and efficiently by a MATLAB procedure.The proposed model is also used in forecasting for an urgent problem in Vietnam.This application also shows the advantages of the proposed model and illustrates its effectiveness in practical application.
文摘This study proposes some results in classifying by Bayesian method. There are upper and lowerbounds of the Bayes error as well as its determination in case of one dimension and multidimensions. Based on the proposals for estimating of probability density functions, calculatingthe Bayes error and determining the prior probability, we establish an algorithm to evaluateability of customers to pay debts at banks. This algorithm has been performed by the Matlabprocedure that can be applied well with real data. The proposed algorithm is tested by the realapplication at a bank in Viet Nam that obtains the best results in comparing with the existingapproaches.
