• Proceedings of the Korea Society for Simulation Conference
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• 2002.05a
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• pp.253-258
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• 2002

This paper proposes a methodology for development of protocol models. The methodology attempts to employ two modeling environments in models development, NS2 and DEVSim++, which will interoperate during simulation. NS2 is a widely used network simulator in protocol research, which employs an informal modeling approach. Within the approach time and state information of protocol models are not explicitly described, thus being hard to validate model. On the other hand the DEVS formalism is a mathematical framework for modeling a discrete event system in a hierarchical, modular manner. In DEVS, model's time and state information is described explicitly, By using DEVS formalism, models can easily be validated and errors in the modeling stage can be reduced. However, the DEVS simulator, DEVSim++, supports a small amount of models library which are required to build simulation models of general communication network. Although NS2 employs an informal modeling approach and models validation is difficult, it supports abundant models library validated by experimental users. Thus, combination of DEVS models and NS2 models may be an effective solution for network modeling. Such combination requires interoperation between DEVSim++ simulator and NS2 simulator. This paper develops an environment for such interoperation. Correctness and effectiveness of the implemented interoperation environment have been validated by simulation of UDP and TCP models.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.73-83
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• 2007

Network modeling of irrigation system that links irrigation facilities with stream is necessary to establish complicated rural water management system and to manage agricultural water effectively. This study attempted a network modeling for an agricultural water district called "ANGO" located in Anseongcheon watershed by connecting ArcHydro Model developed to control geographical information data in the field of water resources and AWDS(Agricultural Water Demand & Supply Estimation System) developed by KRC (Korea Rural Community & Agriculture Corporation). Network modeling was embodied by build topology between spatial objects of total 70 agricultural irrigation facilities (24 reservoirs, 18 pumping stations, 28 weirs) and stream network using ArcHydro Model. In addition, new menus were added in ArcGIS system for query and visualization of text-based AWDS outputs such as irrigation facilities information, water demand and supply analysis.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.2
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• pp.13-26
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• 2001

This paper presents the network security modeling methodology and simulation using the hierarchical and modular modeling and simulation framework. Recently, Howard and Amoroso developed the cause-effect model of the cyber attack, defense, and consequences, Cohen has been proposed the simplified network security simulation methodology using the cause-effect model, however, it is not clear that it can support more complex network security model and also the model-based cyber attack simulation. To deal with this problem, we have adopted the hierarchical and modular modeling and simulation environment so called the System Entity Structure/Model Base (SES/MB) framework which integrates the dynamic-based formalism of simulation with the symbolic formalism of AI. Several simulation tests performed on sample network system verify the soundness of our method.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.141-148
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• 2016

In this paper, we propose a topic network analysis approach which integrates topic modeling and social network analysis. We collected 2,039 scientific papers from five top journals in the field of data mining published from 1996 to 2015, and analyzed them with the proposed approach. To identify topic trends, time-series analysis of topic network is performed based on 4 intervals. Our experimental results show centralization of the topic network has the highest score from 1996 to 2000, and decreases for next 5 years and increases again. For last 5 years, centralization of the degree centrality increases, while centralization of the betweenness centrality and closeness centrality decreases again. Also, clustering is identified as the most interrelated topic among other topics. Topics with the highest degree centrality evolves clustering, web applications, clustering and dimensionality reduction according to time. Our approach extracts the interrelationships of topics, which cannot be detected with conventional topic modeling approaches, and provides topical trends of data mining research fields.

• 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.2
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• pp.182-189
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• 2016

A modeling method of electric power network inside a fishing boat less than 5 tons is proposed for its high-energy efficiency with renewable energy sources. The power network inside the fishing boat consists of a diesel engine, a starter motor, an alternator, battery packs, and electric loads, which are connected in parallel. To obtain proper power network model, the voltage -current characteristics of the electric components are considered to develop elaborate electrical models under several load conditions. Measured data of the battery and alternator current include noise. By using an average method, the AC components from the power network of the fishing boat can be reduced, which is verified by KCL rule. Using the proposed power network model, the power generation of the alternator and the reduction of diesel consumption in the boat's engine are predictable under various operating conditions. The validity of the proposed methodology is verified by comparing simulation results with experimental measurements using statistical inferences.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.327-330
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• 2007

This article discusses a capacity planning method in QoS-guaranteed IP networks such as BcN (Broadband convergence Network). Since IP based networks have been developed to transport best-effort data traffic, the introduction of multi-service component in BcN requires fundamental modifications in capacity planning and network dimensioning. In this article, we present the key issues of the capacity planning in multi-service IP networks. To provide a foundation for network dimensioning procedure, we describe a systematic approach for classification and modeling of BcN traffic based on the QoS requirements of BcN services. We propose a capacity planning framework considering data traffic and real-time streaming traffic separately. The multi-service Erlang model, an extension of the conventional Erlang B loss model, is introduced to determine required link capacity for the call based real-time streaming traffic. The application of multi-service Erlang model can provide significant improvement in network planning due to sharing of network bandwidth among the different services.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1103-1120
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• 2015

A self-sensing magnetorheological (MR) damper with embedded piezoelectric force sensor has recently been devised to facilitate real-time close-looped control of structural vibration in a simple and reliable manner. The development and characterization of the self-sensing MR damper are presented based on experimental work, which demonstrates its reliable force sensing and controllable damping capabilities. With the use of experimental data acquired under harmonic loading, a nonparametric dynamic model is formulated to portray the nonlinear behaviors of the self-sensing MR damper based on NARX modeling and neural network techniques. The Bayesian regularization is adopted in the network training procedure to eschew overfitting problem and enhance generalization. Verification results indicate that the developed NARX network model accurately describes the forward dynamics of the self-sensing MR damper and has superior prediction performance and generalization capability over a Bouc-Wen parametric model.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.791-793
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• 2000

The fuzzy inference system is a popular computing framework based on the concepts of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. The advantage of fuzzy approach over traditional ones lies on the fact that fuzzy system does not require a detail mathematical description of the system while modeling. As modeling method. the Group Method of Data Handling(GMDH) is introduced by A.G. Ivakhnenko GMDH is an analysis technique for identifying nonlinear relationships between system's inputs and output. We study a Novel Neuro-Fuzzy Network (NNFN) in this paper. NNFN is a network resulting from the combination of a fuzzy inference system and polynomial neural network(PNN) (7) which is advanced structure of GMDH. Simulation involve a series of synthetic as well as experimental data used across various neurofuzzy systems.

• Journal of Information Technology Services
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• v.2 no.2
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• pp.97-109
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• 2003

As the importance and the need for network security is increased, many organization uses the various security systems. They enable to construct the consistent integrated security environment by sharing the vulnerable information among firewall, intrusion detection system, and vulnerable scanner. And Policy-based network provides a means by which the management process can be simplified and largely automated. In this article we build a foundation of policy-based network modeling environment. The procedure and structure for policy rule induction from vulnerabilities stored in SVDB (Simulation based Vulnerability Data Based) is conducted. It also transforms the policy rules into PCIM (Policy Core Information Model).