• IE interfaces
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• v.17 no.2
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• pp.142-148
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• 2004

The objective of bridge construction cost allocation is to distribute in a fair and rational manner the bridge construction costs among those vehicles using the bridge. In most bridge construction cost allocation studies, bridge construction costs are mainly distributed according to traffic load(gross vehicle weight), without any consideration of bridge capacity requirements(the number of lanes). In this paper, a bridge cost allocation method for considering both traffic capacity and traffic loads is developed. The proposed method is based on cooperative game theory, particularly two concepts known as the Aumann-Shapley (A-S) value and Shapley value. This method can help to analyze the impact of traffic capacity costs. By applying the proposed method to an example, traffic capacity cost is found to be high so that traffic capacity should be considered to allocate the bridge construction costs to vehicle classes in a more equitable manner.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.16-22
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• 2013

This paper proposes a new concept of comonotonicity of uncertain vector based on the uncertainty theory. In order to understand the comonotonicity of uncertain vector, some equivalent definitions are presented. Following the proposed concept, some basic properties of comonotonic uncertain vector are investigated. In addition, the operational law is given for calculating the uncertainty distributions of monotone functions of comonotonic uncertain variables. With the help of operational law, the comonotonic uncertain vector is applied to the premium pricing problems. At last, some numerical examples are given to illustrate the application.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.122-127
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• 2001

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

• Journal of the Korean Society of Combustion
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• v.8 no.1
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• pp.46-56
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• 2003

The present paper is concerned with the development of the computational biology in the past half century and its relationship with combustion. The modem computational biology is considered to be initiated by the work of Alan Turing on the morphogenesis in 1952. This paper first touches the life and scientific achievement of Alan Turing and his theory on the morphogenesis based on the reactive-diffusive instability, called the Turing instability. The theory of Turing instability was later extended to the nonlinear realm of the reactive-diffusive systems, which is discussed in the framework of the excitable media by using the Oregonator model. Then, combustion analogies of the Turing instability and excitable media are discussed for the cellular instability, pattern forming combustion phenomena and flame edge. Finally, the recent efforts on numerical simulations of biological systems, employing the detailed bio-chemical knietic mechanism is discussed along with the possibility of applying the numerical combustion techniques to the computational cell biology.

• Knowledge Management Research
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• v.9 no.3
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• pp.141-158
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• 2008

This study introduces the construct of group efficacy and combines the construct with the Adaptive Structuration Theory(AST) and user satisfaction framework. Job efficacy and IT efficacy identified as the dimensions of group efficacy are hypothesized to influence faithfulness of appropriation and consensus on appropriation. and then the user satisfaction of knowledge management systems(KMS). Data were collected through a survey of respondents who have the experience of using KMS, and analyzed by using structural equations modelling. The major findings of this study are as follows: First, job efficacy was found to have a positive influence on consensus on appropriation and user satisfaction. Second, IT efficacy was found to have a positive effect on faithfulness of appropriation and consensus on appropriation. Third, faithfulness of appropriation was found to have a positive influence on consensus on appropriation and user satisfaction. Implications of these findings are discussed for researchers and practitioners.

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.60-63
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• 1988

An adaptive model following controller is designed using the theory of variable structure systems. The proposed method allows the designer to satisfy the requirements of short sliding plane reaching time and chattering reduction in the sliding mode. This method is based on the modified condition for the sliding mode. The result of computer simulation shows that state trajectories reach switching plane fast and chattering is reduced.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.7
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• pp.79-86
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• 1992

Recent research on the application of fuzzy set theory to the design of control systems has led to interest in the theory of decomposition of multivariable fuzzy systems. Decomposition of multivariable control rules is preperable since it alleviates the complexity of the problem. However inference error is inevitable because of its approximate nature. In this paper we define an index of applicability which can classify whether the Gupta et. al's method can be applied to multivariable fuzzy system or not. We also propose a modified version of the decomposition which can reduce inference error and improve performance of the system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.170-174
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• 1997

This paper studies a method for making more efficient classification rules in the ID3 using the rough set theory. Decision tree technique of the ID3 always uses all the attributes in a table of examples for making a new decision tree, but rough set technique can in advance eleminate dispensable attributes. And the former generates only one type of classification rules, but the latter generates all the possibles types of them. The rules generated by the rough set technique are the simplist from as proved by the rough set theory. Therefore, ID3, applying the rough set technique, can reduct the size of the table of examples, generate the simplist form of the classification rules, and also implement an effectie classification system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.104-112
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• 2001

Simply, Nonlinear dynamics theory means the complicated and noise-like phenomena originated form nonlinearity involved in deterministic dynamical system. An almost all the natural signals have nonlinear property. However, there exist few analysis software tool or package for a research and development of applications. We develop nonlinear time series analysis simulator is to provide a common and useful tool for this purpose and to promote research and development of nonlinear dynamics theory. This simulator is consists of the following four modules such as generation module, preprocessing module, analysis module and ICA module. In this paper, we applied to Electroencephalograph (EEG), as it turned out, our simulator is able to analyze nonlinear time series. Besides, we could get the useful results using the various parameters. These results are used to diagnostic the brain diseases.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.666-674
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• 2001

Classical methods to find a minimal set of rules based on the rough set theory are known to be ineffective in dealing with new instances added to the universe. This paper introduces an inductive learning algorithm for incrementally retrieving a minimal set of rules from a given decision table. Then, the algorithm is validated via simulations with two sets of data, in comparison with a classical non-incremental algorithm. The simulation results show that the proposed algorithm is effective in dealing with new instances, especially in practical use.