• The Journal of the Acoustical Society of Korea
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• v.21 no.3E
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• pp.105-111
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• 2002

The parabolic equation technique provides an excellent model to describe the wave phenomena when there exists a predominant direction of propagation. The model handles the square root wave number operator in paraxial direction. Realization of the pseudo-differential square root operator is the essential part of the parabolic equation method for its numerical accuracy. The wide-angled approximation of the operator is made based on the Pade series expansion, where the branch line rotation scheme can be combined with the original Pade approximation to stabilize its computational performance for complex modes. The Galerkin integration has been employed to discretize the depth-dependent operator. The benchmark tests involving the half-infinite space, the range independent and dependent environment will validate the implemented numerical model.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.259-262
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• 1997

In this paper, a fuzzy model based on the polynomial Neural Network(PNN) structure is proposed to estimate the emission pattern for air pollutant in power plants. The new algorithm uses PNN algorithm based on Group Method of Data Handling (GMDH) algorithm and fuzzy reasoning in order to identify the premise structure and parameter of fuzzy implications rules, and the least square method in order to identify the optimal consequence parameters. Both time series data for the gas furnace and data for the NOx emission process of gas turbine power plants are used for the purpose of evaluating the performance of the fuzzy model. The simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy anhd feasibility than other works achieved previously.

• 한국기계연구소 소보
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• s.10
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• pp.49-62
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• 1983

A series of model tests on a container ship in waves was executed at the Experimental Towing Tank of Ship Research Station, KIMM. This paper presents the results of resistance, self-propulsion, propeller open-water and ship motion tests in regular head waves. Firstly, the experimental results of ship motion measured on a towed model and a self-propelled model were compared with those of Japanese results showing fairly good agreements. Secondly, the results of resistance and propulsion tests were analyzed and the data of added resistance, thrust increase, torque increase, revolution increase and self-propulsion factors in waves were presented. Also the diffraction force measured on a fixed model in waves was analyzed. Finally, this report shows the propeller characteristics in calm water based on propeller immersion and in regular waves based on wave length.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.39-42
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• 2002

For the purpose of modeling EEG signal which has nonstationary and nonlinear dynamic characteristics, this paper propose a state feedback real time recurrent neural network model. The state feedback real time recurrent neural network is structured to have memory structure in the state of hidden layers so that it has arbitrary dynamics and ability to deal with time-varying input through its own temporal operation. For the model test, Mackey-Glass time series is used as a nonlinear dynamic system and the model is applied to the prediction of three types of EEG, alpha wave, beta wave and epileptic EEG. Experimental results show that the performance of the proposed model is better than that of other neural network models which are compared in this paper in some view points of the converging speed in learning stage and normalized mean square error for the test data set.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.420-423
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• 2001

In this paper, the Multi-FNNs(Fuzzy-Neural Networks) architecture is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNNs architecture uses simplified inference and linear inference as fuzzy inference method and error back propagation algorithm as learning rules. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNNs according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNNs model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model we use the time series data for gas furnace and the NOx emission process data of gas turbine power plant.

• Proceedings of the KIEE Conference
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• 2004.07e
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• pp.110-113
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• 2004

PV model is presented based on the shockley diode equation. The simple model has a photo-current source, an single diode junction and a series resistance and includes temperature dependences. An accurate PV module electrical model is presented, matching with boost converter MPPT strategy and demosnstarted in Matlab for a typical general purpose solar cell. Given solar insolation and temperature, the model returns current vector and MPP.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.100.3-100
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• 2001

This article deals with the development of a mathematical model for the finishing polycarbonate polymerization process using a horizontal rotating disk-ring reactor with counter-current gas sweeping and the performance analysis of the reactor system by using the model. Here we intend to propose a model describing the reactor system consisting of two phases, in which by-product phenol is removed from the polymer of high molecular weight compatible with the products of commercial grades. The vapor phase is represented by a tanks-ln-series model while the polymer melt phase is regarded as a plug flow reactor.

• 한국전산유체공학회:학술대회논문집
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• 2003.10a
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• pp.197-199
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• 2003

In this work, the Greitzer's B-parameter model is applied for analyzing the stall and surge characteristics. The four parameters in the model are highlighted in order to establish the influence of each parameter on the system. First of all, the governing equations of stall and surge behavior are solved numerically using fourth-order Runge-Kutta method. The Taguchi method is then used to analyze the results generated to obtain the extent of effects of the parameters on the system by varying the parameters in a series of combinations. Finally, a thorough analysis is carried out on the results generated from the Taguchi method and the graphs.

• Asia-Pacific Journal of Business
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• v.7 no.1
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• pp.1-10
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• 2016

This study attempts to investigate the effects of different types of debts on economic growth in Bangladesh using time series data spanning from 2000 to 2015. In this study, the RDL model has been applied to determine the long run relationship among the selected variables. The result of the ARDL model shows that there exists a long term relationship between economic growth and the debt variables. It was evident from the findings that there exists bidirectional causality between public sector external debt and economic growth. Causality between private external debt and economic growth has been found to be insignificant. However, causality between domestic debt and economic growth showed a unidirectional causality from domestic debt to economic growth and not vice versa. Causality tests suggest that impact of domestic debt on economic growth is more effective compared to external debts.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.172-176
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• 2000

A series of preliminary experiments were carried out to quantify the annoyance are noisiness caused by floor impact noise. From the results of the experiments. the heavy impact source was found to be felt louder and noisier than the light impact source. Measurements of noise were also conducted by a diagnostic system based on the model(the model consists of the autocorrelators and the cross-correlation for signals arriving at two ear entrants) of the human auditory-brain system. Physical factors in the model were calculated by use of the ACF(autocorrelation function) and IACF(interaural cross correlation function) of binaural signals. From the ACF/IACF analysis, it was found that perceived loudness of floor impact noise could be represented by the factors of the ACF/IACF model.