• Water for future
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• v.29 no.5
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• pp.223-233
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• 1996

Daily streamflow model, DAWAST, considering the meteorologic and geographic characteristics of the Korean watersheds has been developed to simulate the daily streamflow with the input data of daily rainfall and pan evaporation. The model is the conceptual one with three sub-models which are optimization, generalization, and regionalization models. The conceptual model consists of three linear reservoirs representing the surface, unsaturated, and saturated soil zones and water balance analysis was carried out in each soil zones on a daily basis. Optimization model calibrates the parameters by optimization technique and is applicable to the watersheds where the daily streamflow data are available Generalization model predicts the parameters by regression equations considering the geographic, soil type, land use, and hydrogeologic characteristics of watershed and is appicable to ungaged medium or small watersheds. Regionalization model cites the parameters from the analysed ones considering river system, latitude and longitude, and is applicable to ungaged large watersheds.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.111-127
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• 2007

The logistic distribution is generalized using the Marshall-Olkin scheme and its generalization. Some properties are studied. First order autoregressive time series model with Marshall-Olkin semi-logistic distribution as marginal is developed and studied.

• Journal of the Korean Statistical Society
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• v.19 no.1
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• pp.45-53
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• 1990

Factorization models are a generalization of hierarchical loglinear models which apply equally to discrete and continuous distributions. In regular (strictly positive) cases the intersection of two factorization models is another factorization model whose representation is obtained by a simple algorithm. Failure of this result in an irregular case is related to a theorem of Basu on ancillary statistics.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1557-1560
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• 1997

In this paper, we have built an experimental magnetic levitation system for a possible use of control education. We have give a mathermatical model of the nonlinear system and have shown the stability region of the linearized system when it is controlled by a PD controller. We also proposed a neural network control system which uses a neural network as a feedforward controller thgether with a conventional feedback PF controller. We have generated a desired output trajectory, which was designed for the benefit of the generalization of the neural network controller, and trained the desired output trajectory, which was desigend for the benefit of the generalization of the neural netowrk controller, and trained a neural network controller with the data of the actual input and the output of the system obtained by applying the desired output trajectroy. A good tracking performance was observed for both the desired trajectiories used and not used for the neural network training.

• Management Science and Financial Engineering
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• v.16 no.3
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• pp.95-102
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• 2010

This paper considers the robust inventory control problem introduced by Bertsimas and Thiele [4]. In their paper, they have shown that the robust version of the inventory control problem can be solved by solving a nominal inventory problem which is formulated as a mixed integer program. As a proper generalization of the model, we consider the problem with non-stationary cost. In this paper, we show that the generalized version can also be solved by solving a nominal inventory problem. Furthermore, we show that the problem can be solved efficiently.

• The Transactions of the Korea Information Processing Society
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• v.5 no.1
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• pp.11-23
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• 1998

In very large databases, the problem of searching for interesting information effectively is very important in terms of efficiency and flexibility. A multiple layered database approach based on AOG(attribute-oriented generalization) method is one of the useful approaches for knowledge discovery under various situations. In this paper, we propose a multiple layered database design methodology based on AOG method in object-oriented databases. In addition, we propose a dynamic schema evolution model and implementation strategy in order to continue providing information effectively in multiple layered databases.

• Journal of The Korean Astronomical Society
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• v.18 no.2
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• pp.86-99
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• 1985

A generalization of the original ${\ddot{O}}pik's$ cellular convection theory has been made to accomodate a rotating convective medium. With the use of the formulation, a set of rotating model envelopes of the sun and late type main sequence stars have been constructed under three different rotation periods. Their thermal structures are presented and characteristics of their convection are discussed in the context of stellar dynamo. In the present study it is noted that the rotational angular velocity increases in wards with depth, and its increase turns out to be about 6% at the bottom of the solar convection zone.

• Proceedings of the IEEK Conference
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• summer
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• pp.5-9
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• 2004

This paper proposed a systematic analysis for slotted ALOHA with capture effect. This is a generalization for slotted ALOHA system. Based on this model, we can increase the maximum through-put of slotted ALOHA system with two power levels. Lee's algorithm is consider to be an extension of ALOHA system with capture effect. In this paper, we showed that, the choice of Lee's algorithm is not an optimum one. Based on the previous experimental results, we proposed here a more practical analysis for slotted ALOHA system. The result is very accurate and can be applied to other wireless systems which also employed capture effect.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.4
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• pp.271-276
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• 2006

To implement a generalization of value functions in Adaptive Search Element (ASE)-reinforcement learning, CMAC (Cerebellar Model Articulation Controller) is integrated into ASE controller. ASE-reinforcement learning scheme is briefly studied to discuss how CMAC is integrated into ASE controller. Neighbourhood Sequential Training for CMAC is utilized to establish the look-up table and to produce discrete control outputs. In computer simulation, an ASE controller and a couple of ASE-CMAC neural network are trained to balance the inverted pendulum on a cart. The number of trials until the controllers are established and the learning performance of the controllers are evaluated to find that generalization ability of the CMAC improves the speed of the ASE-reinforcement learning enough to realize the cartpole control system.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.422-432
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• 2019

A hybrid kernel function of support vector machine is proposed to improve the classification performance of power quality disturbances. The kernel function mathematical model of support vector machine directly affects the classification performance. Different types of kernel functions have different generalization ability and learning ability. The single kernel function cannot have better ability both in learning and generalization. To overcome this problem, we propose a hybrid kernel function that is composed of two single kernel functions to improve both the ability in generation and learning. In simulations, we respectively used the single and multiple power quality disturbances to test classification performance of support vector machine algorithm with the proposed hybrid kernel function. Compared with other support vector machine algorithms, the improved support vector machine algorithm has better performance for the classification of power quality signals with single and multiple disturbances.