• IE interfaces
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• v.11 no.1
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• pp.85-95
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• 1998

This study is focussed on an optimal vehicle routing model for multi-supply centers in two-echelon logistic system. The aim of this study is to deliver goods for demand sites with optimal decision. This study investigated an integrated model using step-by-step approach based on relationship that exists between the inventory allocation and vehicle routing with restricted amount of inventory and transportations such as the capability of supply centers, vehicle capacity and transportation parameters. Three sub-models are developed: 1) sector-clustering model, 2) a vehicle-routing model based on clustering and a heuristic algorithm, and 3) a vehicle route scheduling model using TSP-solver based on genetic and branch-and-bound algorithm. Also, we have developed computer programs for each sub-models and user interface with visualization for major inputs and outputs. The application and superior performance of the proposed model are demonstrated by several sample runs for the inventory-allocation and vehicle routing problems.

• Water Engineering Research
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• v.1 no.3
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• pp.243-256
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• 2000

This physically-based hydrologic model is developed to calculate the soil-moisture balance on paddy fields. This model consists of three modules; the first is the unsaturated module, the second is the rice evapotranspiration module with SPAC(soil-plant-atmospheric-continuum), and the third is the groundwater and open channel flows based upon the interrehtionship module. The model simulates the hydrlogical processes of infiltration, soil water storage, deep perocolation or echarge to the shallow water table, transpiration and evaporation from the soil surface and also the interrelationship of the groundwater and river flow exchange. To verify the applicability of the developed model, it was applied to the Kimjae Plains, located in the center of the Dongjin river basin in Korea, during the most serious drought season of 1994. The result shows that the estimated water net requirement was 757mm and the water deficit was about 5.9% in this area in 1994. This model can easily evaluate the irrigated water quantity and visualize the common crop demands and soil moisture conditions.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.111-117
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• 2008

This paper presents a new continuation-based quasi-steady-state(CQSS) time-domain simulation algorithm incorporating a multiplicative aggregated load model for power systems. The authors' previous paper introduced a CQSS algorithm, which has the robust convergent characteristic near the singularity point due to the application of a continuation method. The previous CQSS algorithm implemented the load restoration in power systems using the exponent-based load recovery model that is derived from the additive dynamic load model. However, the reformulated exponent-based model causes the inappropriate variation of short-term load characteristics when switching actions occur, during time-domain simulation. This paper depicts how to incorporate a multiplicative load restoration model, which does not have the problem of deforming short-term load characteristics, into the time simulation algorithm, and shows an illustrative example with a 39-bus test system.

• Korean Journal of Computational Design and Engineering
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• v.11 no.6
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• pp.429-439
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• 2006

The purpose of this study is to support the integration from current 2D drawing-based design to future 3D model-based design. In this paper, an important theme is the combination between the STEP-based 2D drawing standards (i.e., AP202) and the IFC-based 3D building model standards. To achieve the purpose, two methodologies are proposed as follows: the development of IFC extension model for the 2D shape data representation by harmonizing ISO/STEP AP202; and the development of mapping solution between IFC 2D extension model and KOSDIC by constructing the exchange scenario for 2D shape data representation. It is expected that the proposed IFC2X2 2D extension model and mapping solution will offer the basis of development of the integrated standards model in AEC industry.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.123-128
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• 1998

This paper proposes design of LFT-based fuzzy controllers for model-following, which are better than the previous input-output linearization controllers, which are not able to follow the model system states and which do not guarantee the stability of all states. The method proposed in this paper provides a LFT-based Takagi-Sugeno(T-S) fuzzy controller with guaranteed stability and model-following via the following steps: First, using LFT(Linear Fractional Transformation) and T-S fuzzy model, controllers, are obtained. Next, error dynamics are obtained for model-following, and errors go to 0(zero). Finally, a T-s fuzzy controller that can stabilizxe the system with the requirement on the control input satisfied is obtained by solving the LMIs with the MATLAB LMI Control Toolbox and a model-following controller is obtained. Simulations are performed for the LFT-based T-S fuzzy controller designed by the proposed method, which show better performance than the results of input-out ut linearization controller.

• International Journal of Highway Engineering
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• v.15 no.5
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• pp.31-45
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• 2013

PURPOSES : Determination of particle packing model variables that can be used for formulation of new DEM based particle packing model by examining existing particle packing models METHODS : Existing particle packing models are thoroughly examined by analytical reformulation and sensitivity analysis in order to set up DEM based new particle packing model and to determine its variables. All model equations considered in this examination are represented with consistent expressions and are compared to each others to find mathematical and conceptual similarity in expressions. RESULTS : From the examination of existing models, it is observed that the models are very similar in their shapes although the derivation of the models may be different. As well, it is observed that variables used in some existing models are comprehensive enough to estimate particle packing but not applicable to DEM simulation. CONCLUSIONS : A set of variables that can be used in DEM based particle packing model is determined.

• Smart Media Journal
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• v.12 no.5
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• pp.9-16
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• 2023

In the recommendation system of the credit card company, it is necessary to understand the customer patterns to predict a customer's next merchant based on their histories. The data we want to model is much more complex and there are various patterns that customers choose. In such a situation, it is necessary to use an effective model that not only shows the relevance of the merchants, but also the relevance of the customers relative to these merchants. The proposed model aims to predict the next merchant for the customer. To improve prediction performance, we propose a novel model, called Customer-based Recommendation Model (CRM), to produce a more efficient representation of customers. For the next merchant recommendation system, we use a synthetic credit card usage dataset, BC'17. To demonstrate the applicability of the proposed model, we also apply it to the next item recommendation with another real-world transaction dataset, IJCAI'16.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.183-188
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• 2012

One of the major challenge for retrieval performance is the word mismatch between user's queries and documents in information retrieval. To solve the word mismatch problem, we propose a retrieval model based on the degree of association of query concept and word translation probabilities in translation-based model. The word translation probabilities are calculated based on the set of a sentence and its succeeding sentence pair. To validate the proposed method, we experimented on TREC AP test collection. The experimental results show that the proposed model achieved significant improvement over the language model and outperformed translation-based language model.

• The Journal of Information Systems
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• v.27 no.3
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• pp.63-80
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• 2018

Purpose The purpose of this study is to build a machine learning-based customer classification model to promote customer expansion effect of the free sample promotion. Specifically, the proposed model classifies potential target customers who are expected to purchase the products included in the free sample promotion after receiving the free samples. Design/methodology/approach This study proposes to build a customer classification model for determining customers suitable for providing free samples by using various machine learning techniques such as logistic regression, multiple discriminant analysis, case-based reasoning, decision tree, artificial neural network, and support vector machine. To validate the usefulness of the proposed model, we apply it to a real-world free sample-based target marketing case of a Korean major cosmetic retail company. Findings Experimental results show that a machine learning-based customer classification model presents satisfactory accuracy ranging from 70% to 75%. In particular, support vector machine is found to be the most effective machine learning technique for free sample-based target marketing model. Our study sheds a light on customer relationship management strategies using free sample promotions.

• Structural Engineering and Mechanics
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• v.61 no.4
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• pp.463-473
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• 2017

Reinforced concrete is a complex material to be modeled in finite element domain. A proper material model is necessary to represent the nonlinear behaviour accurately. Though the nonlinear analysis of RC structures evolved long back, still an accurate and reliable model to predict the realistic behaviour of components are limited. It is observed from literature that there are three well-known models to represent the nonlinear behaviour of concrete. These models include Chu model (1985), Hsu model (1994) and Saenz model (1964).A new stress-strain model based on Weibull distribution has been proposed in the present study. The objective of the present study is to analyze a reinforced concrete beam under flexural loading by employing all the models. Nonlinear behaviour of concrete is considered in terms of stress vs. strain, damage parameter, tension stiffening behaviour etc. The ductility of the RC beams is computed by using deflection based and energy based concepts. Both deflection ductility and energy based ductility is compared and energy based concept is found to be in good correlation with the experiments conducted. The behavior of RC beam predicted using ABAQUS has been compared with the corresponding experimental observations. Comparison between numerical and experimental results confirms that these four constitutive models are reliable in predicting the behaviour of RC structures and any of the models can be employed for analysis.