• Journal of the Korea Society for Simulation
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• v.22 no.4
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• pp.67-82
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• 2013

This paper presents multi-fidelity modeling and simulation (M&S) methodology to enhance simulation performance of engineering-level defense models. In this approach, a set of models with varying degrees of fidelity is exercised to reduce computational expense maintaining a similar level of system effectiveness. For multi-fidelity M&S principles, this paper defines model fidelity from two perspectives (i.e., model behavior and execution), and suggests the Fidelity Change Point (FCP) to specify the fidelity conversion. With these concepts, this paper centers on three ideas: 1) two models' structure which are the Behavioral-Fidelity Interchangeable Model (B-FIM) and the Executional-Fidelity Interchangeable Model (E-FIM), 2) modeling formalism, and 3) a simulation algorithm to support them. From an abstract case study regarding a target tracking scenario with the utilization of the proposed method, we can gain interesting experimental results regarding the enhancement of simulation performance. Finally, we expect that this work will serve various M&S-based analysis areas for enhancing simulation performance.

• Journal of Korea Water Resources Association
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• v.38 no.11
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• pp.907-916
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• 2005

For an urban watershed modeling, the ILLVDAS and SWMM model were the popular rainfall-runoff models using in Korea. However, combined sewerage systems in urban area produce some problems when a flood event happens because of the surcharged precipitation amounts which drain to streams directly. Also, rack of pipe line data and difficulties of modeling yield inappropriate modeling results in urban runoff analysis. In addition, rainfall-runoff models in an urban which using channel routing could be inaccurate and complicated processes. In this paper, the MIKE SWMM model has been applied for a stable urban area runoff analysis. Watershed and pipe line data were established by using past inundated records, DEM data and numerical pipe line data. For a runoff modeling, the Runoff block was adapted to a basin and the Extran block using dynamic equation was applied for sewerage system. After a comparisons against existing models yield that the MIKE SWMM model produce reliable and consistence results without distorting parameter of the model.

• Korean System Dynamics Review
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• v.10 no.3
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• pp.25-45
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• 2009

The concept of social capital has recently been highlighted in most fields of social science because social capital is believed to be an alternative of market and government failures. However, social capital is of high ambiguity that hinders in conceptualizing and modeling that can differs from the premises, such as whether social capital lies in individual actors or collective substances, or whether social networks are functioning by rationality or emotion. This study therefore tries to examine the concept of social capital and suggest 6 types of it following by the anthropologic concept of 'reciprocity' as well as to provide fruitful discussions on the introduction of social capital variables to System Dynamics modeling of sustainable development. Conclusively, the introduction of social capital to the integration models of environment-economy-society should be based on strongly understanding the social networks, individual identities, and local particularities of the relevant localities in order to enhance the structural validity and applicability of sustainable development models in System Dynamics.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.3
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• pp.765-774
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• 1996

Computer Integrated Manufacturing(CIM) requires models of manufacturing processes to be implemented on the computer. These models are typically used for determining optimal process control parameters or designing adaptive control systems. In spite of the progress made in the mechanistic modeling, however, empirical models derived from experimental data play a maior role in manufacturing process modeling. This paper describes the development of a meural metwork medel for injection molding. This paper describes the development of a nueral network model for injection molding process. The model uses the CAE analysis data based on Taguchi method. The developed model is, then, compared with the traditional polynomial regression model to assess the applicabilit in practice.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2121-2142
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• 2011

In this paper, we propose an e-Learning process control model that aims to graphically describe and automatically generate the manifest of sequencing prerequisites in packaging SCORM's content aggregation models. In specifying the e-Learning activity sequencing, SCORM provides the concept of sequencing prerequisites to be manifested on each e-Learning activity of the corresponding tree-structured content organization model. However, the course developer is required to completely understand the SCORM's complicated sequencing prerequisites and other extensions. So, it is necessary to achieve an efficient way of packaging for the e-Learning content organization models. The e-Learning process control model proposed in this paper ought to be an impeccable solution for this problem. Consequently, this paper aims to realize a new concept of process-driven e-Learning content aggregating approach supporting the e-Learning process control model and to implement its e-Learning process modeling system graphically describing and automatically generating the SCORM's sequencing prerequisites. Eventually, the proposed model becomes a theoretical basis for implementing a SCORM-based e-Learning process management system satisfying the SCORM's sequencing prerequisite specifications. We strongly believe that the e-Learning process control model and its modeling system achieve convenient packaging in SCORM's content organization models and in implementing an e-Learning management system as well.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.3
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• pp.21-31
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• 2007

This study is aimed at the development of a runoff forecasting model by using the Fuzzy inference system and Neural Network model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting. The Neuro-Fuzzy (NF) model were used in this study. The NF model, recently received a great deal of attention, improve the existing Neural Networks by the aid of the Fuzzy theory applied to each node. The study area is the downstreams of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model respectively. The schematic diagram method and the statistical analysis are conducted to evaluate the feasibility of rainfall-runoff modeling. The model accuracy was rapidly decreased as the forecasting time became longer. The NF model can give accurate runoff forecasts up to 4 hours ahead in standard above the Determination coefficient $(R^2)$ 0.7. In the comparison of the runoff forecasting using the NF and TANK models, characteristics of peak runoff in the TANK model was higher than ones in the NF models, but peak values of hydrograph in the NF models were similar.

• Geomechanics and Engineering
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• v.6 no.4
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• pp.391-401
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• 2014

In an attempt to make a numerical modeling of the nailed walls with a view to assess the stability has been used. A convenient modeling which can provide answers to nearly situ conditions is of particular significance and can significantly reduce operating costs and avoid the risks arising from inefficient design. In the present study, a nailing system with a excavation depth of 8 meters has been modeled and observed by using the three constitutive behavioral methods; Mohr Coulomb (MC), hardening soil (HS) and hardening soil model with Small-Strain stiffness ensued from small strains (HSS). There is a little difference between factor of safety and the forces predicted by the three models. As extremely small lateral deformations exert effect on stability and the overall deformation of a system, the application of advanced soil model is essential. Likewise, behavioral models such as HS and HSS realize lower amounts of the heave of excavation bed and lateral deformation than MC model.

• Coupled systems mechanics
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• v.8 no.6
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• pp.489-500
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• 2019

With drinking water standards becoming more rigorous and increasing demands for additional water quantities, while water resources are becoming more polluted, mathematical models became an important tool to improve water treatment processes performance in the water supply system. Water treatment processes models reflect the knowledge of the processes and they are useful tools for water treatment process optimization, design, operator training for decision making and fundamental research. Unfortunately, in the current practice of drinking-water production and distribution, water treatment processes modeling is not successfully applied. This article presents a review of some existing water treatment processes simulators and the experience of their application and indicating the main weak points of each process. Also, new approaches in the modeling of water treatment are presented and recommendations are given for the work in the future.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.511-527
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• 2016

We propose a rotating stereo frame camera system to acquire indoor images with a low cost. For experiments, we selected a test site and acquired images using the proposed system and control points using a total station. Using these data, we generated various indoor 3D models using commercial photogrammetric software, PhotoScan. We then performed qualitative and quantitative analysis of the generated indoor 3D models to investigate the possibility of the indoor modeling using the proposed system. From the results, it is confirmed that the generated indoor models using the proposed system can be applicable to the services not inquiring high accuracy.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.324-334
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• 2016

Manufacturers and retailers are interested in how prices, promotions, discounts and other marketing variables can influence the sales and shares of the products that they produce or sell. Therefore, many models have been developed to predict the brand share. Since the customer choice models are usually used to predict the market share, here we use hybrid model of Probabilistic Neural Network and Artificial Bee colony Algorithm (PNN-ABC) that we have introduced to model consumer choice to predict brand share. The evaluation process is carried out using the same data set that we have used for modeling individual consumer choices in a retail coffee market. Then, to show good performance of this model we compare it with Artificial Neural Network with one hidden layer, Artificial Neural Network with two hidden layer, Artificial Neural Network trained with genetic algorithms (ANN-GA), and Probabilistic Neural Network. The evaluated results show that the offered model is outperforms better than other previous models, so it can be use as an effective tool for modeling consumer choice and predicting market share.