• 한국시뮬레이션학회논문지
• /
• 제5권2호
• /
• pp.25-40
• /
• 1996

Modeling of systems for intensive knowledge-based processing requires a modeling methodology that makes efficient access to the information in huge data base models. The proposed level access mothodology is a modeling approach applicable to systems where data is stored in a hierarchical and modular modules of active memory cells(processor/memory pairs). It significantly reduces the effort required to create discrete event simulation models constructed in hierarchical, modular fashion for above application. Level access mothodology achieves parallel access to models within the modular, hierarchical modules(clusters) by broadcasting the desired operations(e.g. querying information, storing data and so on) to all the cells below a certain desired hierarchical level. Level access methodology exploits the capabilities of object-oriented programming to provide a flexible communication paradigm that combines port-to-port coupling with name-directed massaging. Several examples are given to illustrate the utility of the methodology.

• 한국시뮬레이션학회논문지
• /
• 제9권4호
• /
• pp.41-50
• /
• 2000

We have many simulation constraints to meet as a modeled system becomes large and complex. Real-time simulations are the examples in that they are constrained by certain non-function constraints (e.g., timing constraints). In this paper, an enhanced hierarchical modeling methodology is proposed to efficiently deal with constraint-simulations. The proposed modeling method enhances hierarchical modeling methods to provide multi-resolution model. A simulation model is composed by determining the optimal level of abstraction that is guaranteed to meet the given simulation constraints. Four modeling activities are defined in the proposed method: 1) Perform the logical architectural design activity to produce a multi-resolution model, 2) Organize abstraction information of the multi-resolution model with AT (Abstraction Tree) structure, 3) Formulate the given constraints based on U (Integer Programming) approach and embrace the constraints to AT, and 4) Compose a model based on the determined level of abstraction with which the multi-resolution model can satisfy all given simulation constraints. By systematically handling simulation constraints while minimizing the modeler's interventions, we provide an efficient modeling environment for constraint-simulations.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
• /
• pp.204-208
• /
• 2001

In this paper, we induce the linear transfer function of Downcomer water level of NPP(Nuclear Power Plant) Steam Generator using Genetic Algorithm and Levenberg-Marquardt Algorithm. The characteristic of NPP S/G mechanism is so high-non-linear that it is hard to achieve mathematical expression. So we use non-mathematical Algorithms to get the model function of NPP S/G water level. S/G level controller would be designed with this transfer function as the plant.

• 산업공학
• /
• 제8권3호
• /
• pp.61-73
• /
• 1995

As the level of maunfacturing system automation increases, the issues of modeling and simulation of AMS(Automated Manufacturing System) are becoming more important. Proposed in this paper is the JR-Net(Job Resource relation-Net) modeling framework which naturally mimics the process of designing an AMS by FA(Factory Automation) engineers. Its main purpose is to provide a modeling tool which facilitate modeling work of AMS for FA engineers unfamiliar with simulation modeling. The proposed modeling scheme is based on the extensive observation that typical AMSs are built from the set of 'standard' components(or catalog items). As an application of the proposed model, two real examples of FMS('G7'FMS model plant, RPI FMS) are modeled by JR-Net, and in case of FMS model plant, a simulation program development procedure using JR-Net modeling results is explained. Finally, simulation result of FMS model plant is analyzed.

• 한국응용과학기술학회지
• /
• 제32권4호
• /
• pp.649-660
• /
• 2015

Calpuff 역모델링 기법을 이용해 산출된 자료는 오염물질 발생량을 예측할 수 있으며, 여러 가지 자료 비교를 통해 감축 가능성 및 목표 수립이 가능해졌다. 본 연구에서는 동해항 주변지역을 대상으로 Calpuff 역모델링 기법을 이용하여 대기 중 미세먼지 저감량 설정하기 위한 기초자료 구축에 목적을 두었으며, 모델링을 이용한 동해항을 포함한 5개 지역 배출농도 산출결과는 다음과 같다. 대기환경기준인 $50{\mu}g/m^3$을 적용하여 대상 지역별 허용배출량 산출 결과 site-D에서 가장 많은 $4.95{\mu}g/m^2{\cdot}S$의 배출량 저감이 요구되었으며, $4.95{\mu}g/m^2{\cdot}S$의 배출량을 감소시킬 경우 영향예측지점(동해하수종말처리장)의 PM10 평균 예측농도는 $42.6{\mu}g/m^3$로 감소될 것으로 나타났다. site-A(동해항)에서 배출되는 오염물질만을 적용하여 모델링 진행 결과 동해항 주변 민가의 기여농도는 평균 $40{\sim}50{\mu}g/m^3$으로 나타났으며, 배경농도를 고려하면 대기환경기준인 $50{\mu}g/m^3$을 상회 할 것으로 예상됨에 따라 더 이상의 오염물질 배출량은 허용되지 않을 것으로 판단된다. site-B는 상가와 나대지로 차량 통행과 나대지에서 비산되는 먼지로 인해 $0.11{\mu}g/m^2{\cdot}S$의 배출량 저감이 요구되었으며, site-C와 E는 오염물질 저감량은 발생하지 않았으나 지속적인 관리가 요구된다.

• Journal of Positioning, Navigation, and Timing
• /
• 제13권1호
• /
• pp.63-73
• /
• 2024

NeQuick G is the ionosphere model utilized by Galileo single-frequency users to estimate the ionospheric delay on each user-satellite link. The model is characterized by the effective ionization level (Az) index, determined by a modified dip latitude (MODIP) and broadcast coefficients derived from daily global space weather observations. However, globally fitted Az coefficients may not accurately represent ionosphere within local area. This study introduces a method for regional ionospheric modeling that searches for locally optimized Az coefficients. This approach involves fitting TEC output from NeQuick G to TEC data collected from GNSS stations around Korea under various ionospheric conditions including different seasons and both low and high solar activity phases. The optimized Az coefficients enable calculation of the Az index at any position within a region of interest, accounting for the spatial variability of the Az index in a polynomial function of MODIP. The results reveal reduced TEC estimation errors, particularly during high solar activity, with a maximum reduction in the RMS error by 85.95%. This indicates that the proposed method for NeQuick G can effectively model various ionospheric conditions in local areas, offering potential applications in GNSS performance analyses for local areas by generating various ionospheric scenarios.

• International Journal of Computer Science & Network Security
• /
• 제21권9호
• /
• pp.247-260
• /
• 2021

Data modeling is a process of developing a model to design and develop a data system that supports an organization's various business processes. A conceptual data model represents a technology-independent specification of structure of data to be stored within a database. The model aims to provide richer expressiveness and incorporate a set of semantics to (a) support the design, control, and integrity parts of the data stored in data management structures and (b) coordinate the viewing of connections and ideas on a database. The described structure of the data is often represented in an entity–relationship (ER) model, which was one of the first data-modeling techniques and is likely to continue to be a popular way of characterizing entity classes, attributes, and relationships. This paper attempts to examine the basic ER modeling notions in order to analyze the concepts to which they refer as well as ways to represent them. In such a mission, we apply a new modeling methodology (thinging machine; TM) to ER in terms of its fundamental building constructs, representation entities, relationships, and attributes. The goal of this venture is to further the understanding of data models and enrich their semantics. Three specific contributions to modeling in this context are incorporated: (a) using the TM model's five generic actions to inject processing in the ER structure; (b) relating the single ontological element of TM modeling (i.e., a thing/machine or thimac) to ER entities and relationships; and (c) proposing a high-level integrated, extended ER model that includes structural and time-oriented notions (e.g., events or behavior).

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
• /
• pp.155-157
• /
• 2005

We propose a new category of hybrid multi-layer neural networks with hetero nodes such as Fuzzy Set based Polynomial Neurons (FSPNs) and Polynomial Neurons (PNs). These networks are based on a genetically optimized multi-layer perceptron. We develop a comprehensive design methodology involving mechanisms of genetic optimization and genetic algorithms, in particular. The augmented genetically optimized HFPNN (namely gHFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of HFPNN leads to the selection of preferred nodes (FPNs or PNs) available within the HFPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFPNNs quantified through experimentation where we use a number of modeling benchmarks-synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling.

• International Journal of Computer Science & Network Security
• /
• 제21권4호
• /
• pp.103-114
• /
• 2021

A conceptual model can be used to manage complexity in both the design and implementation phases of the system development life cycle. Such a model requires a firm grasp of the abstract principles on which a system is based, as well as an understanding of the high-level nature of the representation of entities and processes. In this context, models can have distinct architectural characteristics. This paper discusses model multiplicity (e.g., unified modeling language [UML]), model singularity (e.g., object-process methodology [OPM], thinging machine [TM]), and a heterogeneous model that involves multiplicity and singularity. The basic idea of model multiplicity is that it is not possible to present all views in a single representation, so a number of models are used, with each model representing a different view. The model singularity approach uses only a single unified model that assimilates its subsystems into one system. This paper is concerned with current approaches, especially in software engineering texts, where multimodal UML is introduced as the general-purpose modeling language (i.e., UML is modeling). In such a situation, we suggest raising the issue of multiplicity versus singularity in modeling. This would foster a basic appreciation of the UML advantages and difficulties that may be faced during modeling, especially in the educational setting. Furthermore, we advocate the claim that a multiplicity of views does not necessitate a multiplicity of models. The model singularity approach can represent multiple views (static, behavior) without resorting to a collection of multiple models with various notations. We present an example of such a model where the static representation is developed first. Then, the dynamic view and behavioral representations are built by incorporating a decomposition strategy interleaved with the notion of time.

• Advances in Computational Design
• /
• 제4권2호
• /
• pp.91-118
• /
• 2019

Every year, many people are severely injured or lose their lives in accidents such as fire, chemical spill, public pandemonium, school shooting, and workplace violence. Research indicates that the fate of people in an emergency situation involving one or more hazards depends not only on the design of the space (e.g., residential building, industrial facility, shopping mall, sports stadium, school, concert hall) in which the incident occurs, but also on a host of other factors including but not limited to (a) occupants' characteristics, (b) level of familiarity with and cognition of the surroundings, and (c) effectiveness of hazard intervention systems. In this paper, we present EVAQ, a simulation framework for modeling large crowd evacuation by taking into account occupants' behaviors and interactions during an emergency. In particular, human's personal (i.e., age, gender, disability) and interpersonal (i.e., group behavior and interactions) attributes are parameterized in a hazard-impacted environment. In addition, different hazard types (e.g., fire, lone wolf attacker) and propagation patterns, as well as intervention schemes (simulating building repellent systems, firefighters, law enforcement) are modeled. Next, the application of EVAQ to crowd egress planning in an airport terminal under human attack, and a shopping mall in fire emergency are presented and results are discussed. Finally, a validation test is performed using real world data from a past building fire incident to assess the reliability and integrity of EVAQ in comparison with existing evacuation modeling tools.