• Journal of Korea Water Resources Association
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• v.45 no.11
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• pp.1169-1186
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• 2012

Storage function method has been used for flood forecasting in the major rivers in Korea, however, the researches on the relationship between the parameters and runoff characteristics was not sufficient. In addition, there has been a controversy about the optimized parameters without the consideration of the physical characteristics of the basin. Therefore, in this study, the SCE-UA method is used to optimize the parameters and the proposed method was applied with two stage optimization in the Jeongseon and Yeongwol watersheds located in the most upstream in the South Han river. The contour map was developed to investigate parameters and the error surface calculated from the runoff. The proposed parameters is to provide a range of the possible parameter set in a watershed, rather than a specific value. However, the applicability is examined using the average value of the proposed ranged parameters. In this study, the criticism about the optimization technique to find an optimal value having no physical meaning on a watershed is tried to avoid. The objective of this study is to provide a range of parameters for the flood forecasting model and the intuition about the behavior of the parameters, so the efficiency of flood forecasting is increased.

• Korean Journal of Construction Engineering and Management
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• v.15 no.4
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• pp.68-76
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• 2014

The accurate estimation of construction cost is important to a successful development in construction projects. In previous studies, the construction cost are estimated by statistical methods. Among the statistical methods, support vector regression (SVR) has attracted a lot of attentions because of the generalization ability in the field of cost estimation. However, despite the simplicity of the parameter to be adjusted, it is not easy to find optimal parameters. Therefore, to build an effective SVR model, SVR's parameters must be set properly without additional data handling loads. So this study proposes a novel approach, known as genetic algorithm (GA), which searches SVR's optimal parameters, then adopt the parameters to the SVR model for estimating cost in the early stage of apartment housing projects. The aim of this study is to propose a GA-SVR model and examine the feasibility in cost estimation by comparing with multiple regression analysis (MRA). The experimental results demonstrate the estimating performance based on the percentage of estimations within 25% and find it can effectively do the accurate estimation without through the trial and error process.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.723-729
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• 2001

Electro-hydraulic shift control of a vehicle automatic transmission has been predominantly carried out via an open-loop control based on numerous time-consuming calibrations. Despite remarkable success in practice, the variations of system characteristics inevitably deteriorate the performance of the tuned open-loop controller. As a result, the controller parameters need to be continuously updated in order to maintain satisfactory shift quality. This paper presents a self-learning algorithm for automatic transmission shift control in a construction vehicle during inertia phase. First, an observer reconstructs the turbine acceleration signal (impossible to measure in a construction vehicle) from the readily accessible turbine speed measurement. Then, a control algorithm based on a quadratic function of the turbine acceleration is shown to guarantee the asymptotic convergence (within a specified target bound) of the error between the actual and the desired turbine accelerations. A Lyapunov argument plays a crucial role in deriving adaptive laws for control parameters. The simulation and hardware-in-the-loop simulation (HILS) studies show that the proposed algorithm actually delivers the promise of satisfactory performance despite the system characteristics variations and uncertainties.

• Smart Structures and Systems
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• v.29 no.3
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• pp.433-444
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• 2022

Concrete is a most utilized material in the construction industry that have main components. The strength of concrete can be improved by adding some admixtures. Evaluating the impact of fly ash (FA) and silica fume (SF) on the long-term compressive strength (CS) of concrete provokes to find the significant parameters in predicting the CS, which could be useful in the practical works and would be extensible in the future analysis. In this study, to evaluate the effective parameters in predicting the CS of concrete containing admixtures in the long-term and present a fitted equation, the multivariate adaptive regression splines (MARS) method has been used, which could find a relationship between independent and dependent variables. Next, for optimizing the output equation, biogeography-based optimization (BBO), particle swarm optimization (PSO), and hybrid PSOBBO methods have been utilized to find the most optimal conclusions. It could be concluded that for CS predictions in the long-term, all proposed models have the coefficient of determination (R²) larger than 0.9243. Furthermore, MARS-PSOBBO could be offered as the best model to predict CS between three hybrid algorithms accurately.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.475-478
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• 2013

To carry out a one-off construction project successfully, effective and accurate early cost estimation is crucial, especially during the conceptual stage where very limited minimum information of construction project is given. As the level of accuracy of the early cost estimation has huge impacts on precise budgeting and cost management of a project, in other words, reducing the risk of a project, cost must be managed with special awareness. In an effort to improve the estimate accuracy of cost during the conceptual stage, this research introduces a Parameter Impact (PI) which can quantify weights of parameters and rank them; and PI development derived from the principle of impulse in physics is explicated. For a case study, 76 public apartment building cases in Korea are analyzed. To examine the validity of the proposed PI, a validation in terms of CBR applicability test and estimate accuracy comparisons using 10-nearest neighbor cases are carried out. The validation results support that the suggested PI can be applied in quantifying the weights of the parameters and CBR method for early cost estimation.

• Geomechanics and Engineering
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• v.36 no.6
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• pp.601-618
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• 2024

The joint probability distribution of uncertain geomechanical parameters of geotechnical strata is a crucial aspect in constructing the reliability functional function for roof structures. However, due to the limited number of on-site exploration and test data samples, it is challenging to conduct a scientifically reliable analysis of roof geotechnical strata. This study proposes a Copula method based on small sample exploration and test data to construct the intensity characteristics of roof geotechnical strata. Firstly, the theory of multidimensional copula is systematically introduced, especially the construction of four-dimensional Gaussian copula. Secondly, data from measurements of 176 groups of geomechanical parameters of roof geotechnical strata in 31 coal mines in China are collected. The goodness of fit and simulation error of the four-dimensional Gaussian Copula constructed using the Pearson method, Kendall method, and Spearman methods are analyzed. Finally, the fitting effects of positive and negative correlation coefficients under different copula functions are discussed respectively. The results demonstrate that the established multidimensional Gaussian Copula joint distribution model can scientifically represent the uncertainty of geomechanical parameters in roof geotechnical strata. It provides an important theoretical basis for the study of reliability functional functions for roof structures. Different construction methods for multidimensional Gaussian Copula yield varying simulation effects. The Kendall method exhibits the best fit in constructing correlations of geotechnical parameters. For the bivariate Copula fitting ability of uncertain parameters in roof geotechnical strata, when the correlation is strong, Gaussian Copula demonstrates the best fit, and other Copula functions also show remarkable fitting ability in the region of fixed correlation parameters. The research results can offer valuable reference for the stability analysis of roof geotechnical engineering.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.483-488
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• 2008

The exhaust system, including a muffler, is one of the major sources to generate the radiated noise of construction equipment. In general, the muffler is applied to construction equipment in order to reduce the exhaust noise. Sometimes, however, the higher exhaust noise can be experienced due to the flow effect inside a muffler. So, it is required to consider the flow effect to reduce the exhaust noise level of construction equipment. In this paper, various tests were performed to calculate the flow noise effect inside a muffler. Through a series of tests with respect to a variety of design parameters, a new design program for low noise muffler was developed and applied to reduce the exhaust noise of the construction equipments. These results make it possible to understand the dynamic characteristics of the flow noise and to design the low noise muffler for the construction equipments.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.4
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• pp.45-52
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• 2010

The purposes of this research are to analyze the internal settlement behavior of Concrete Faced Rockfill Dam (CFRD) typed 'D dam' and to evaluate the stability of the 'D dam' during dam construction using internal settlement measurements and results of numerical analysis. The field measurements were obtained during dam construction period. The numerical analysis was also carried out for the same construction period. The numerical analysis focused mainly on prediction of stress and displacement behavior of 'D dam' during dam construction stage using input parameters obtained from laboratory tests, i.e. large triaxial tests. The behavior of 'D dam' was evaluated to be stable from comparing the results of field measurements and numerical analysis. A simple empirical equation is also presented to predict final settlement at the completion of dam construction, using settlement measurement monitored during dam embankment.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.967-975
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• 2009

In order to control differential settlement and to secure the safety of super structure on a high rock embankment the designed static compaction is changed with dynamic compaction and piled raft method. The parameters for dynamic compaction design are obtained from a pilot test. In addition, numerical analyses are also carried out to figure out the length and quantity of piled raft that can restraint the differential settlement within allowance range.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.25-39
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• 2010

Recently, GIS softwares such as WMS, ArcHydro, and HyGIS which can calculate hydrological geographic parameters are popularized. These softwares have the functions to calculate various geographic parameters which are used in water resources from DEM (Digital Elevation Model). In this study, hydrological geographic parameters calculated by WMS and ArcHydro are compared and examined with them from HyGIS to evaluate the applicability of the parameters from HyGIS. Bochungcheon (Riv.), Wicheon (Riv.), Pyungchanggang (Riv.), Gyungancheon (Riv.), Naerincheon (Riv.), and Imjingang (Riv.) watersheds are selected for this study, and the shape of watershed, watershed area, watershed slope, the average slope of watershed, main stream length, main stream slope, maximum flow distance, and the slope of maximum flow distance are calculated to compare and examine the characteristics. Study results show that the average relative error of 7 geographic parameters from all the watersheds is 4.77 %, and all the watershed boundaries are very similar. So, all the geographic parameters calculated by each software show very similar value, and the geographic parameters calculated by HyGIS can be applied to water resources with WMS and ArcHydro which have been generally used.