• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.121-131
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• 2014

Traffic speed is an important measure in transportation. It can be employed for various purposes, including traffic congestion detection, travel time estimation, and road design. Consequently, accurate speed prediction is essential in the development of intelligent transportation systems. In this paper, we present an analysis and speed prediction of a certain road section in Busan, South Korea. In previous works, only historical data of the target link are used for prediction. Here, we extract features from real traffic data by considering the neighboring links. After obtaining the candidate features, linear regression, model tree, and k-nearest neighbor (k-NN) are employed for both feature selection and speed prediction. The experiment results show that k-NN outperforms model tree and linear regression for the given dataset. Compared to the other predictors, k-NN significantly reduces the error measures that we use, including mean absolute percentage error (MAPE) and root mean square error (RMSE).

• Journal of Navigation and Port Research
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• v.29 no.5 s.101
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• pp.409-413
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• 2005

The existing control techniques for the operation of a container crane satisfy the terminal condition of controlled variables, but the outcome of input computation is inadequate for the operation of the crane due to heavy movement of inputs. In this study, a new control technique employing a nonlinear model of the crane is proposed to compute the inputs approximated with the 4th-order Chevyshev function. The control objective of sum of absolute deviations is minimized, and the optimization is conducted with the simplex algorithm. The inputs and outputs computed from the proposed technique were compared with the results of the previous study to show that they give more stable crane operation than the existing control technique.

• Korean Chemical Engineering Research
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• v.50 no.1
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• pp.155-161
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• 2012

A dynamic biofilter model was suggested to integrate the effect of biofilter-medium adsorption capacity on the removal efficiency of volatile organic compound (VOC) contained in waste air. In particular, the suggested biofilter model is composed of four components such as biofilm, gas phase, sorption volume and adsorption phase and is capable of predicting the unsteady behavior of biofilter-operation. The process-lumping model previously suggested was limited in the application for the treatment of waste air since it was derived under the assumption that the adsorbed amount of VOC equilibrated with biofilter-media would be proportional to the concentration of dissolved VOC in the sorption volume of biofilter-media. Therefore a Freundlich adsorption isotherm was integrated into a robust biofilter process-lumping model applicable to a wide range of VOC concentration. The values of model parameters related to biofilter-medium adsorption were obtained from the dynamic adsorption column experiments in the preceding article and literature survey. Furthermore a separate biofilter experiment was conducted to treat waste air containing ethanol and the experimental result was compared with the model predictions with various values of Thiele modulus (${\phi}$). The obtained value of Thiele modulus (${\phi}$) was close to 0.03.

• Tunnel and Underground Space
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• v.27 no.5
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• pp.303-311
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• 2017

The correlation analysis between the results obtained from DFN flow model and equivalent continuum flow model were conducted on total of 72 DFN blocks having various fracture geometry and domain size. A strong linear relation seems to exist between the two approaches under condition that normalized relative error for continuum behavior (ER) is less than 0.2, and the results from both methods are found to almost identical. To explore the field applicability of equivalent continuum flow model in DFN media, a total of 48 numerical schemes related to inflow of underground circular openings were implemented under various DFN configurations. The equivalent continuum flow model in DFN media with a constant hydraulic aperture was evaluated as valid. However, as the anisotropy increases due to variation of the hydraulic aperture, the results are likely to be overestimated compare to the DFN flow model.

• Korean Chemical Engineering Research
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• v.52 no.5
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• pp.574-580
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• 2014

Storage tanks of Carbon dioxide ($CO_2$) carriers utilized for the purpose of carbon capture and storage (CCS) into subsea strata have to undergo a pre-cooling session before beginning to load cryogenic liquid cargos in order to prevent physical and thermal deterioration of tanks which may result from cryogenic $CO_2$ contacting tank walls directly. In this study we propose dynamic model to calculate the tank inflow of $CO_2$ gas injected for precooling process and its dynamic simulation results under proportional-integral control algorithm. We selected two cases in which each of them had one controlled variable (CV) as either the tank pressure or the tank temperature and discussed the results of that decision-making on the pre-cooling process. As a result we demonstrated that the controlling instability arising from nonlinearity and singularity of the mathematical model could be avoided by choosing tank pressure as CV instead of tank temperature.

• Journal of the Korea Concrete Institute
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• v.23 no.2
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• pp.245-252
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• 2011

Currently, the design guidelines for the prevention of progressive collapse are not available in Korea due to the lack of study efforts in progressive collapse resistance evaluation of RC flat plate system. Therefore, in this study, three types of analysis were conducted to evaluate the progressive collapse resistance of a RC flat plate system. A linear static analysis was carried out by comparing the demand-capacity ratio (DCR) differences of the systems using the alternate load path method, which is the guideline of GSA. A dynamic behavior was investigated by checking the vertical deflection after removal of the column using the linear dynamic analysis. Lastly, a maximum load factor was investigated using the nonlinear static analysis. The finite element (FE) analyses were conducted using various parameters to analyze the results obtained using effective beam width (EB) model and plate element FEM (PF) model. This study results showed that the strength contributions of the slab in the EB models are underestimated compared to those obtained from the PF models. Therefore, a detailed FE analysis considering the slab element is required to thoroughly estimate the progressive collapse resisting capacity of flat plate system. The scenario of the corner column (CC) removal is the most dangerous conditions where as the scenario of the inner column (IC) removal is the least dangerous conditions based on the consideration of various parameters. The analysis results will allow more realistic evaluations of progressive collapse resistance of RC flat plate system.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.31 no.1
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• pp.121-126
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• 1998

This study is to examine the energy budget of Hexagrammos agrammus in the natural habitat, based on the von Bertalanffy's growth model using food consumption and growth data of the fish. The fish were collected at the coasts of Tongbaek Island in Pusan and Shinsu Island in Samchonpo, Korea. The standard energy budget model was adopted for this study and the model has the components of toed consumption (C), production (G), assimilation (A), absorption ($A_b$), catabolism (R), excreta (U) and feces (F). These components were expressed as mass unit, not as calorie unit as usual. Both the mass and the proportion of each component varied with age of the fish, The mass of annual excreta declined as the fish became older, while those of the other components increased with the age. The relationship between mean weight (W) and annual absorption ($A_b$) was a non-linear one with the equation of $A_b=4.592W^{0.666}$, while that between mean weight (W) and annual catabolism (R) was linear as R=0.007+0.567W. On the other hand, the annual food consumption (C) showed linear relations both with annual assimilation (A) and annual catabolism (R) as A= -7.026+0.061C and R=-20.749+0.048C, respectively.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1143-1155
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• 1999

셀룰러 방식의 이동통신 시스템에서 전파의 유효신호 도달범위를 예측하기 위해서는 전파전파 모델을 이용한 예측기법이 주로 사용된다. 그러나, 전파과정에서 주변 지형지물에 의해 발생하는 전파손실은 매우 복잡한 비선형적인 특성을 가지며 수식으로는 정확한 표현이 불가능하다. 본 논문에서는 신경회로망의 함수 근사화 능력을 이용하여 전파손실 예측모델을 생성하는 방법을 제안한다. 즉, 전파손실을 송수신 안테나간의 거리, 송신안테나의 특성, 장애물 투과영향, 회절특성, 도로, 수면에 의한 영향 등과 같은 전파환경 변수들의 함수로 가정하고, 신경회로망 학습을 통하여 함수를 근사화한다. 전파환경 변수들이 신경회로망 입력으로 사용되기 위해서는 3차원 지형도와 벡터지도를 이용하여 전파의 반사, 회절, 산란 등의 물리적인 특성이 고려된 특징 추출을 통해 정량적인 수치들을 계산한다. 이와 같이 얻어진 훈련데이타를 이용한 신경회로망 학습을 통해 전파손실 모델을 완성한다. 이 모델을 이용하여 서울 도심 지역의 실제 서비스 환경에 대한 타 모델과의 비교실험결과를 통해 제안하는 모델의 우수성을 보인다.Abstract In cellular mobile communication systems, wave propagation models are used in most cases to predict cell coverage. The amount of propagation loss induced by the obstacles in the propagation path, however, is a highly non-linear function, which cannot be easily represented mathematically. In this paper, we introduce the method of producing propagation loss prediction models by function approximation using neural networks. In this method, we assume the propagation loss is a function of the relevant parameters such as the distance from the base station antenna, the specification of the transmitter antenna, obstacle profile, diffraction effect, road, and water effect. The values of these parameters are produced from the field measurement data, 3D digital terrain maps, and vector maps as its inputs by a feature extraction process, which takes into account the physical characteristics of electromagnetic waves such as reflection, diffraction and scattering. The values produced are used as the input to the neural network, which are then trained to become the propagation loss prediction model. In the experimental study, we obtain a considerable amount of improvement over COST-231 model in the prediction accuracy using this model.

• Journal of Korean Society of Forest Science
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• v.90 no.3
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• pp.324-330
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• 2001

This study was carried out to develop prediction model for fill slope failure of forest road in igneous rock area using fuzzy theory which is non-linear model. The results were summarized as follows. The importance weight of factors on fill slope failure was ranked in the order of fill slope length, fill slope gradient, soil type, aspect, road position and longitudinal slope form. The degree of potential slope failure was high mainly under the such conditions as fill slope length greater than 8m, fill slope gradients steeper than $40^{\circ}$, constituent material with weathered rock, aspect of NE and road on ridge position. The optimal prediction model was developed with 0.15 of optimal coefficient(c) and 3.1165 of ${\lambda}$-value when fuzzy integral value of slope failure possibility is more than 0.5. And the discriminant accuracy was 86.8%, which shows the high availability for discrimination.

• Journal of Navigation and Port Research
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• v.31 no.3 s.119
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• pp.247-252
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• 2007

The container crane is one of the most important equipments at container terminal. If its working time in cycle could be reduced then container terminal efficiency and service level can be increased. So there are many i1forts to reduce working time of container cranes. It means how to design the controller with good performance which has small overshoot and swing motion of container crane. We, in this paper, present a state feedback controller based on LQ theory incorporating a RCGA which means real-coded genetic algorithm RCGA can search state feedback gains under given objective function. A set of simulation works are carried out in order to prove the control effectiveness of the proposed methods.