• Journal of Biomedical Engineering Research
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• v.16 no.4
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• pp.415-424
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• 1995

Combined models, specified by two or more modeling formalisms, can represent a wide variety of complex systems. This paper describes a methodology for the development of combined models in two model types of discrete event and continuous process. The methodology is based on transformation of continuous state space into discrete one to homomorphically represent dynamics of continuous processes in discrete events. This paper proposes a formal structure which can combine model of the DES and the CS within a framework. The structure employs the DEVS formalism for the DES models and differential or polynomial equations for the CS models. To employ the proposed structure to specify a DEVS/CS combined model, a modeler needs to take the following steps. First, a modeler should identify events in the CS and transform the states of the CS into the DES. Second, a modular employs the formalism to specify the system as the DES. Finally, a moduler developes sub-models for the CS and continguos states of the DES and establishs one-to-one correspondence between the sub-models and such states. The proposed formal structre has been applied to develop a DEVS/CS combined model for the human cardiovascular system. For this, the cardiac cycle is partitioned into a set of phases based on events identified through observation. For each phase, a CS model has been developed and associated with the phase. To validate the DEVS/CS combined model developed, then simulate the model in the DEVSIM + + environment, which is a model simulation results with the results obtained from the CS model simulation using SPICE. The comparison shows that the DEVS/CS combined model adequately represents dynamics of the human heart system at each phase of cardiac cycle.

• Coupled systems mechanics
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• v.10 no.2
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• pp.161-184
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• 2021

Strengthening of reinforced concrete beams with externally bonded fiber reinforced polymer plates/sheets technique has become widespread in the last two decades. Although a great deal of research has been conducted on simply supported RC beams, a few studies have been carried out on continuous beams strengthened with FRP composites. This paper presents a simple uniaxial nonlinear analytical model that is able to accurately estimate the load carrying capacity and the behaviour of damaged RC continuous beams flexural strengthened with externally bonded prestressed composite plates on both of the upper and lower fibers, taking into account the thermal load. The model is based on equilibrium and deformations compatibility requirements in and all parts of the strengthened beam, i.e., the damaged concrete beam, the FRP plate and the adhesive layer. The flexural analysis results and analytical predictions for the prestressed composite strengthened damaged RC continuous beams were compared and showed very good agreement in terms of the debonding load, yield load, and ultimate load. The use of composite materials increased the ultimate load capacity compared with the non strengthened beams. The major objective of the current model is to help engineers' model FRP strengthened RC continuous beams in a simple manner. Finally, this research is helpful for the understanding on mechanical behaviour of the interface and design of the FRP-damaged RC hybrid structures.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.45-48
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• 1999

Model predictive control algorithm requires a relevant model of the system to be controlled. Unfortunately, the first principle model describing a polymerization reaction system has a large number of parameters to be estimated. Thus there is a need for the identification and control of a polymerization reactor system by using available input-output data. In this work, the polynomial auto-regressive moving average (ARMA) models are employed as the input-output model and combined into the nonlinear model predictive control algorithm based on the successive linearization method. Simulations are conducted to identify the continuous styrene polymerization reactor system. The input variables are the jacket inlet temperature and the feed flow rate whereas the output variables are the monomer conversion and the weight-average molecular weight. The polynomial ARMA models obtained by the system identification are used to control the monomer conversion and the weight-average molecular weight in a continuous styrene polymerization reactor It is demonstrated that the nonlinear model predictive controller based on the polynomial ARMA model tracks the step changes in the setpoint satisfactorily. In conclusion, the polynomial ARMA model is proven effective in controlling the continuous styrene polymerization reactor.

• Journal of applied mathematics & informatics
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• v.5 no.3
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• pp.805-810
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• 1998

In this paper we set the stock price model in security market when the price process is a continuous semartingale and find a unigue solution of price process model.

• Industrial Engineering and Management Systems
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• v.15 no.2
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• pp.148-155
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• 2016

Existing power plants may consume significant amounts of fuel and require high operating costs, partly because of poor electrical power output estimates. This paper suggests a continuous conditional random field (C-CRF) model to predict more precisely the full-load electrical power output of a base load operated combined cycle power plant. We introduce three feature functions to model association potential and one feature function to model interaction potential. Together, these functions compose the C-CRF model, and the model is transformed into a multivariate Gaussian distribution with which the operation parameters can be modeled more efficiently. The performance of our model in estimating power output was evaluated by means of a real dataset and our model outperformed existing methods. Moreover, our model can be used to estimate confidence intervals of the predicted output and calculate several probabilities.

• Communications for Statistical Applications and Methods
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• v.19 no.5
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• pp.639-646
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• 2012

The exponential continuous time GARCH(p,q) model for financial assets suggested by Haug and Czado (2007) is considered, where the log volatility process is driven by a general L$\acute{e}$vy process and the price process is then obtained by using the same L$\acute{e}$vy process as driving noise. Uniform ergodicity and ${\beta}$-mixing property of the log volatility process is obtained by adopting an extended generator and drift condition.

• Journal of the Korean Mathematical Society
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• v.58 no.1
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• pp.1-28
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• 2021

We study a continuous data assimilation algorithm for the three-dimensional simplified Bardina model utilizing measurements of only two components of the velocity field. Under suitable conditions on the relaxation (nudging) parameter and the spatial mesh resolution, we obtain an asymptotic in time estimate of the difference between the approximating solution and the unknown reference solution corresponding to the measurements, in an appropriate norm, which shows exponential convergence up to zero.

• Proceedings of the Korea Society for Simulation Conference
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• 2000.11a
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• pp.142-149
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• 2000

Most of supply chain simulation models have been developed on the basis of discrete-event simulation. Since supply chain systems are neither completely discrete nor continuous, the need of constructing a model with aspects of both discrete-event simulation and continuous is provoked, resulting in a combined discrete-continuous simulation. Continuous simulation concerns the modeling over time of a system by a representation in which the state variables change continuously with respect to time. In this paper, an architecture of combined modeling for supply chain simulation is proposed, which presents the equation of continuous part in supply chain and how these equations are used supply chain simulation models. A simple supply chain model is demonstrated the possibility and the capability of this approach.

• The Journal of Information Systems
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• v.26 no.3
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• pp.25-46
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• 2017

Purpose The purpose of this study is to analyze the factors for continuous use intention of the simple payment service based on FinTech for Chinese residents in Korea. The Technology Acceptance Model(TAM) and the continuous use model of information system were applied to the AliPay service, which is the most used by Chinese people. Design/methodology/approach In this study, internal factors and external factors for the simple payment service were derived through previous studies and the effects of the users' perspectives on the intention of continuous use were analyzed. As a result, convenience, responsiveness, perceived usefulness, and suitability were supported as factors affecting ongoing intention to use simple payment service. Especially, convenience is a factor affecting the duration of the simple payment service and it is an important factor for the continuous use of the service. Findings As the number of foreigners living or working in Korea is increasing, understanding the perception of the simple payment service and analyzing the factors for the continuous use can be meaningful as a basic research for the market advancement and growth of domestic FinTech companies is.

• The Transactions of the Korean Institute of Power Electronics
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• v.8 no.2
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• pp.137-142
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• 2003

Two existing continuous-time models for the current-mode control have presented noticeable differences in their small-signal predictions. As an attempt to clarify the origin of these disparities, this paper presents an alternative way of deriving a continuous-time model for the current-model control. The results of this paper would provide insights to comprehend the dissimilarity in the modeling method and final results of the earlier models of current-mode control models.