• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.327-333
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• 2019

Wind speed data constitute important weather information for aircrafts flying at low altitudes, such as drones. Currently, the accuracy of low altitude wind predictions is much lower than that of high-altitude wind predictions. Deep neural networks are proposed in this study as a method to improve wind speed forecast information. Deep neural networks mimic the learning process of the interactions among neurons in the brain, and it is used in various fields, such as recognition of image, sound, and texts, image and natural language processing, and pattern recognition in time-series. In this study, the deep neural network model is constructed using the wind prediction values generated by the numerical model as an input to improve the wind speed forecasts. Using the ground wind speed forecast data collected at the Boseong Meteorological Observation Tower, wind speed forecast values obtained by the numerical model are compared with those obtained by the model proposed in this study for the verification of the validity and compatibility of the proposed model.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.1
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• pp.60-68
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• 2018

A series of tests in an ice tank was carried out using a model-scale ship to investigate the ice loading process. The ship model Uikku was mounted on a rigid carriage and towed through a level ice field in the ice tank of the Marine Technology Group at Aalto University. The carriage speed and ice thickness were varied. In this paper, ice loading process was described and the corresponding ice forces on the horizontal plane were analysed. A new method is proposed to decompose different ice force components from the total ice forces measured in the model tests. This analysis method is beneficial to understanding contributions of each force component and modelling of ice loading on hulls. The analysed experimental results could be used for comparison with further numerical simulations.

• 한국태양에너지학회:학술대회논문집
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• 2009.11a
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• pp.130-135
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• 2009

This study investigates the need of calibrating a nodal network ventilation simulation model (CONTAMW 2.4). For this purpose, the series of ventilation experiments were conducted and then compared to simulation outputs from an uncalibrated simulation model, resulting in a significant difference between two. Hence, an optimization routine was employed to estimate unknown parameters in the simulation model. In the paper, the authors presents 1.3 unknown parameters with the validated simulation model. It was found that the model with estimated unknown parameters predicts the ventilation phenomena accurately.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1560-1563
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• 2010

The goal of this research is to apply the neural networks model for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks model consists of support vector machine neural networks model (SVM-NNM). The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks model, it is composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of SVM-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• Journal of Ocean Engineering and Technology
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• v.18 no.6 s.61
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• pp.51-57
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• 2004

In this study, the improved three-dimensional analysis model designed for a more accurate analysis of marine cable-supported structures, is presented. In this improved analysis model, the beam elements, of which the stability function is derived using Taylor's series expansions, are used to model space frame structures, and the truss elements. The equivalent elastic modulus of the truss elements is evaluated on the assumption that the deflection curve of a cable has a catenary function. By using the proposed three-dimensional analysis model, nonlinear static analysis is carried out for some cable-supported structures. The results are compared with previous studies and show good agreement with their findings.

• Land and Housing Review
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• v.11 no.1
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• pp.59-66
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• 2020

This thesis investigates relationship between Stock-to-Flow price and housing starts in Seoul metropolitan form 2008 year to 2019 year. The paper tests the relationship through two time-series models such as a vector error correction model and Dynamic Panel regression model. The model results show evidence of positive correlation between Stock-to-Flow price and housing starts in the long run. By transforming the regional data into a panel data set and running a fixed effects model, we test the explanatory power of PBR on housing starts. The result of VECM confirms that one unit uprising PBR raises up apartment construction by 7.4%. This result supports that PBR is a major factor in choosing a start of housing construct. Base on the result of empirical model, We also suggest that the market self-regulation function of housing providers is operating in the entire metropolitan area market.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.122-132
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• 1999

This study describes a dynamic model of the hydroforming process which is used for precision forming of sheet metals. To help the controller design for the control of the forming pressure needed for this process as well as to investigate the effect of system parameters on the dynamic behavior, dynamic modeling is performed with emphasis on hydraulic servo system which actuates the forming machine. Since the model contains several unknown parameters, these were estimated via a least square parameter identification method. Based upon the identified model, a series of simulations were performed for various operating conditions. The results were compared with those of the experiments to verify the validity of the proposed model. The comparison study shows that the proposed dynamic model can describe dynamic behavior of the forming pressure of the hydroforming process to desirable accuracy.

• Journal of KSNVE
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• v.10 no.1
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• pp.153-159
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• 2000

This paper presents a new method for including the dynamic stiffness of the stationary parts in rotordynamic analysis. As a consequence of the support dynamics, critical speeds are varied and/or additional critical speeds are introduced. Therefore, dynamic effects of the support are often significant in high speed turbomachinery, but most of analysis has considered the support as a rigid body or a simple structure. The proposed method is based on the coupled characteristics of the driving point and transfer frequency response functions of the support system to model the equivalent spring-mass series in finite element analysis. To demonstrate the applicability of the simulation procedures provided, it is applied to the rotor model of the double suction centrifugal pump. Results of the suggested equivalent-support rotor model including coupled effects agree well with the entire pump model.

• Earthquakes and Structures
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• v.10 no.3
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• pp.629-643
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• 2016

Among all the natural disasters, earthquakes are the most destructive calamities since they cause a plenty of injuries and economic losses leaving behind a series of signs of panic. The present study highlights the moment-curvature relationships for the structural elements such as beam and column elements and Non-Linear Static Pushover Analysis of RC frame structures since it is a very simplified procedure of non-linear static analysis. The highly popular model namely Mander's model and Kent and Park model are considered and then, seismic risk evaluation of RC building has been conducted using SAP 2000 version 17 treating uncertainty in strength as a parameter. From the obtained capacity and demand curves, the performance level of the structure has been defined. The seismic fragility curves were developed for the variations in the material strength and damage state threshold are calculated. Also the comparison of experimental and analytical results has been conducted.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.192-200
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• 2021

In the mid of the December 2019, the virus has been started to spread from China namely Corona virus. It causes fatalities globally and WHO has been declared as pandemic in the whole world. There are different methods which can fit such types of values which obtain peak and get flattened by the time. The main aim of the paper is to find the best or nearly appropriate modeling of such data. The three different models has been deployed for the fitting of the data of Coronavirus confirmed patients in Pakistan till the date of 20^th November 2020. In this paper, we have conducted analysis based on data obtained from National Institute of Health (NIH) Islamabad and produced a forecast of COVID-19 confirmed cases as well as the number of deaths and recoveries in Pakistan using the Logistic model, Gompertz model and Auto-Regressive Integrated Moving Average Model (ARIMA) model. The fitted models revealed high exponential growth in the number of confirmed cases, deaths and recoveries in Pakistan.