• Korean Journal of Logic
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• v.17 no.3
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• pp.399-424
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• 2014

The main objective of this paper is to examine critically White's claim that there is a conflict between Perceptual Dogmatism and Bayesian Theory of Confirmation. For this purpose, this paper is structured as follows: In Section 2, I will introduce White's argument. Section 3 is dedicated to explaining some elements of Bayesian Theory of Confirmation. In particular, I will provide an explanation of confirmation measures and Bayesian Favoring. Using these two conceptual apparatuses, it will be shown that, contrary to what White has thought, there is a way of supporting Perceptual Dogmatism by means of Bayesian Theory of Confirmation - in particular, Bayesian Theory of Favoring.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.238-242
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• 2021

Game theory has been regarded as a useful theoretical tool for modeling the interactions between distinct entities and thus it has been harnessed in various research field. In particular, research attention has been shown to how to apply game theory to modeling the interactions between malign and benign entities in the field of wireless networks. Although various game theoretic modeling work have been proposed in the field of wireless networks, our proposed work is disparate to the existing work in the sense that we focus on mobile malign node detection problem in static wireless sensor networks. More specifically, we propose a Bayesian game theoretic modeling for mobile malign node detection problem in static wireless sensor networks. In our modeling, we formulate a two-player static Bayesian game with imperfect information such that player 1 is aware of the type of player 2, but player 2 is not aware of the type of player 1. We use four strategies in our static Bayesian game. We obtain Bayesian Nash Equilibria with pure strategies under certain conditions.

• 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.

• Journal of Korean Society for Quality Management
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• v.19 no.1
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• pp.72-82
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• 1991

This study deals with the problem of water resources development by using bayesian theory. The purpose of this study is to develop the optimal decision model by applying bayesian theory which determine the optimal alternative in water resources development system. A relevant mathematical model to find an optimal solution formulated and then used in developing an efficient water resources that determine optimal alternative. A numerical example is solved to illustrate the algorithm developed.

• 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 Information Processing Systems
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• v.16 no.2
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• pp.318-328
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• 2020

Letter of Credit (L/C) is currently a very popular international settlement method frequently used in international trade processes amongst countries around the globe. Compared with other international settlement methods, however, L/C has some obvious shortcomings. Firstly, it is not easy to use due to the sophisticated processes its usage involves. Secondly, it is sometimes accompanied by a few risks and some uncertainty. Thus, highly efficient methods need to be used to assess and control these risks. To begin with, FAHP and KMV methods are used to resolve the problem of incomplete information associated with L/C and then, on this basis, Bayesian game theory is used in order to make more scientific and reasonable decisions with respect to international trade.

• Korean Journal of Logic
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• v.16 no.2
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• pp.155-187
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• 2013

The main objective of this paper is to vindicate the Bayesian belief updating rule, i.e. conditionalization. For this purpose, I introduce first what I call Irrelevance Principle, and show that this principle is equivalent to conditionalization. In turn, the principle is vindicated by means of Bayesian confirmation theory. That is, I suggest some theses that Bayesian confirmation theorists should accept, and prove that if Irrelevance Principle is violated, the theses cannot holds.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.77-86
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• 2004

In this study, we applied the Bayesian Network for the case of the mode choice models using the Seoul metropolitan area's house trip survey Data. Sex and age were used lot the independent variables for the explanation or the mode choice, and the relationships between the mode choice and the travellers' social characteristics were identified by the Bayesian Network. Furthermore, trip and mode's characteristics such as time and fare were also used for independent variables and the mode choice models were developed. It was found that the Bayesian Network were useful tool to overcome the problems which were in the traditional mode choice models. In particular, the various transport policies could be evaluated in the very short time by the established relation-ships. It is expected that the Bayesian Network will be utilized as the important tools for the transport analysis.

• Proceedings of the Korean Nuclear Society Conference
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• 1999.10a
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• pp.202.2-202
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• 1999

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.159-167
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• 2009

The vehicles play a significant role in modern people's life as economy grows. The development of car navigation system(CNS) provides various convenience because it shows the driver where they are and how to get to the destination from the point of source. However, the existing map-based CNS does not consider any environments such as traffic congestion. Given the same starting point and destination, the system always provides the same route and the required time. This paper proposes a path planning method with traffic prediction by applying historical driving information to the Fuzzy theory and Bayesian update. Fuzzy theory classifies the historical driving information into groups of leaving time and speed rate, and the traffic condition of each time zone is calculated by Bayesian update. An ellipse area including starting and destination points is restricted in order to reduce the calculation time. The accuracy and practicality of the proposed scheme are verified by several experiments and comparisons with real navigation.