• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.281-285
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• 2005

Learning and evolving are two basics for data mining. As compared with classical learning theory based on objective function with minimizing training errors, the recently evolutionary computing has had an efficient approach for constructing optimal model without the minimizing training errors. The global search of evolutionary computing in solution space can settle the local optima problems of learning models. In this research, combining co-evolving algorithm into statistical learning theory, we propose an co-evolutionary computing for statistical learning theory for overcoming local optima problems of statistical learning theory. We apply proposed model to classification and prediction problems of the learning. In the experimental results, we verify the improved performance of our model using the data sets from UCI machine learning repository and KDD Cup 2000.

• Proceedings of the Safety Management and Science Conference
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• 2005.11a
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• pp.493-504
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• 2005

Statistical Process Control and Process Adjustment theory is gaining recognition in the process industries where the process frequently experiences a shift mean. This paper aims to study, the theory difference between Statistical Process Control and Process Adjustment in simple terms and presents a case study that demonstrates successful integration of Statistical Process Control and Process Adjustment theory for a product in drifting industry.

• International Journal of Quality Innovation
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• v.5 no.1
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• pp.52-67
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• 2004

Successful implementation of statistical process control techniques requires for operational definitions and precise measurements. Nevertheless, very often analysts can dispose of process data available only by linguistic terms, that would be a waste to neglect just because of their intrinsic vagueness. Thus a hybrid approach, which integrates fuzzy set theory and common statistical tools, sounds useful in order to improve effectiveness of statistical process control in such a case. In this work, a fuzzy approach is adopted to manage linguistic information, and the use of a Chi-squared control chart is proposed to monitor process performance.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.197-211
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• 2004

According to the increase of internet application, the marketing process as well as the research and survey, the education process, and administration of government are very depended on web bases. All kinds of goods and sales which are traded on the internet shopping malls are extremely increased. So, the necessity of automatically intelligent information system is shown, this system manages web site connected users for effective marketing. For the recommendation system which can offer a fit information from numerous web contents to user, we propose an automatic recommendation system which furnish necessary information to connected web user using statistical learning theory and bayesian fuzzy clustering. This system is called collaborative CRM in this paper. The performance of proposed system is compared with the other methods using real data of the existent shopping mall site. This paper shows that the predictive accuracy of the proposed system is improved by comparison with others.

• Journal of applied mathematics & informatics
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• v.40 no.1_2
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• pp.191-204
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• 2022

This paper introduces the statistical convergence concepts of double sequences of complex uncertain variables: statistical convergence almost surely(a.s.), statistical convergence in measure, statistical convergence in mean, statistical convergence in distribution and statistical convergence uniformly almost surely(u.a.s.).

• Journal of the Korean Statistical Society
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• v.23 no.2
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• pp.251-269
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• 1994

In this paper we extend Kim and Pollard's cube root asymptotics to other rates of convergence, to establish an asymptotic theory for a multidimensional mode estimator based on uniform kernel with shrinking bandwidths. We obtain rates of convergence depending on shrinking rates of bandwidth and non-normal limit distributions. Optimal decreasing rates of bandwidth are discussed.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.959-966
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• 2000

A dimensionality assessment procedure DETECT uses the property of being near zero of conditional covariances as an indication of unidimensionality .This study provides the convergent properties to zero of conditional covariances when the dta is unidimensional, with which DETECT extends its theoretical grounds.

• Journal for History of Mathematics
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• v.11 no.1
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• pp.68-77
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• 1998

There are two approach methods widely in statistical inferences. First is sampling theory methods and the other is Bayesian methods. In this paper, we will introduce the most basic differences of the two approach methods. Especially, we investigate and introduce the historical origin of Bayesian methods in Statistical inferences which is currently used. Also, we introduce the some characteristics of sampling theory method and Bayesian methods.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.81-93
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• 2015

Validity of the stationary bootstrap of Politis and Romano (1994) is proved for U-statistics under strong mixing. Weak and strong consistencies are established for the stationary bootstrap of U-statistics. The theory is applied to a symmetry test which is a U-statistic regarding a kernel density estimator. The theory enables the bootstrap confidence intervals of the means of the U-statistics. A Monte-Carlo experiment for bootstrap confidence intervals confirms the asymptotic theory.

• Honam Mathematical Journal
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• v.29 no.1
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• pp.83-100
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• 2007

Normality is one of the most common assumptions made in sampling and statistical inference procedures without suffering from lack of attention. Its results may lead to an invalid conclusion. We present several testing procedures that can be used to evaluate the effects of departure from normality using concrete examples by hand or with the aid of Minitab. The goal is to influence prospective teachers in order to learn statistical concepts and techniques for testing normality on the basis of the didactical theory.