• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.144-151
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• 2023

In this study, a database was established by collecting experimental results on various concrete mixtures subjected to freeze-thaw cycles, based on which an artificial neural network-based prediction model was developed to estimate durability resistance of concrete. A regression analysis was also conducted to derive an equation for estimating relative dynamic modulus of elasticity subjected to freeze-thaw loads. The error rate and coefficient of determination of the proposed artificial neural network model were approximately 11% and 0.72, respectively, and the regression equation also provided very similar accuracy. Thus, it is considered that the proposed artificial neural network model and regression equation can be used for estimating relative dynamic modulus of elasticity for various concrete mixtures subjected to freeze-thaw loads.

• Journal of the Korean GEO-environmental Society
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• v.19 no.12
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• pp.47-58
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• 2018

Duncan & Chang(1970) proposed the Duncan-Chang model that a linear relation of transformed stress-strain plots was reconstituted from a nonlinear relation of stress-strain curve of triaxial compression test using hyperbolic theory so as to estimate an initial tangent modulus and ultimate deviator stress for the soil specimen. Although the transformed stress-strain plots show a linear relationship theoretically, they actually show a nonlinearity at both low and high values of strain of the test. This phenomenon indicates that the stress-strain curve is not a complete form of a hyperbola. So, if linear regression analyses for the transformed stress-strain plot are performed over a full range of strain of a test, error in the estimation of their linear equations is unavoidable depending on ranges of strain with non-linearity. In order to reduce such an error, a modified regression analysis method is proposed in this study, in which linear regression analyses for transformed stress-strain plots are performed over the entire range of strain except the range the non-linearity is shown around starting and ending of the test, and then the initial tangent modulus and ultimate deviator stresses are calculated. Isotropically consolidated-drained triaxial compression tests were performed on compacted weathered soil with a modified Proctor density to obtain their model parameters. The modified regression analyses for transformed stress-strain plots were performed and analyzed results are compared with results estimated by 2 points method (Duncan et al., 1980). As a result of analyses, initial tangent moduli are about 4.0% higher and ultimate deviator stresses are about 2.9% lower than those values estimated by Duncan's 2 points method.

• The Journal of Engineering Geology
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• v.19 no.2
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• pp.177-189
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• 2009

The shear strength has been managed as an important factor in soil mechanics. The shear strength estimation model was developed to evaluate the shear strength using only a few soil properties by the linear regression analysis model which is one of the statistical methods. The shear strength is divided into two part; one is the internal friction angle (${\phi}$) and the other is the cohesion (c). Therefore, some valid soil factors among the results of soil tests are selected through the correlation analysis using SPSS and then the model are formulated by the linear regression analysis based on the relationship between factors. Also, the developed model is compared with the result of direct shear test to prove the rationality of model. As the results of analysis about relationship between soil properties and shear strength, the internal friction angle is highly influenced by the void ratio and the dry unit weight and the cohesion is mainly influenced by the void ratio, the dry unit weight and the plastic index. Meanwhile, the shear strength estimated by the developed model is similar with that of the direct shear test. Therefore, the developed model may be used to estimate the shear strength of soils in the same condition of study area.

• Journal of the Korea Computer Industry Society
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• v.2 no.9
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• pp.1191-1198
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• 2001

An increasingly important facet of software development is the ability to estimate the associate cost and effort of development early in the development life cycle. Most of the proposed models are based upon a combination of intuition, expert judgement, and regression analysis of empirical data. Overall, the work has failed to produce any single model that can be applied with a reasonable degree of success to a variety of environments. This paper presents a neural network (NN) model that related software development effort to software size measured in function element types. The heuristic approach is applied to decide the number of hidden neurons in NN from the relationship between input-output pairs. The research describes appropriate NN modeling in the context of a case study for 24 software development projects. Also, this paper compared the NN model with a regression analysis model and found the NN model has better accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.663-670
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• 2019

Corrective thermal performance analysis is required for power plants' turbine cycles to determine the performance status of the cycle and improve the economic operation of the power plant. We developed a sectional classification method for the main feed-water flow to make precise corrections for the performance analysis based on the Performance Test Code (PTC) of the American Society of Mechanical Engineers (ASME). The method was developed for the estimation of the turbine cycle performance in a classified section. The classification is based on feature identification of the correlation status of the main feed-water flow measurements. We also developed predictive algorithms for the corrected main feed-water through a Kernel Regression (KR) model for each classified feature area. The method was compared with estimation using an Artificial Neural Network (ANN). The feature classification and predictive model provided more practical and reliable methods for the corrective thermal performance analysis of a turbine cycle.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.449-449
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• 2022

제주도는 용수의 대부분을 지하수에 의존하므로 지하수위의 예측 및 관리는 매우 중요한 사항이다. 제주도의 지층은 화산활동에 의한 현무암이 겹겹이 쌓여있는 형태를 나타내며 육지의 지층구조와 매우 다른 복잡한 형태를 나타낸다. 이에 따라 제주도 지하수위의 예측은 매우 난해하며, 최근에는 딥러닝 인공지능 모델을 활용하여 지하수위를 예측하는 연구사례가 증가하고 있다. 기존의 연구들은 인공지능 모델들이 지하수위를 적절히 예측한다고 보고하고 있으나 예측의 적절성에 대한 판단기준을 제시하지 못하였으므로 이에 대한 명확한 제시가 필요하다. 본 연구의 목표는 인공지능을 활용한 지하수위 예측오차가 허용 가능한지 판단할 수 있는 기준을 제시함에 있다. 이를 위해 전 세계의 과거 20년 동안 관련 연구결과들을 수집 및 분석하였으며, 분석 결과 인공지능 모델의 지하수위 예측오차는 지하수위 변동성이 큰 지역일수록 증가하는 것을 확인하였다. 이것은 지하수위의 변동형태가 크고 복잡할수록 인공지능 모델의 지하수위 예측성능은 낮아진다는 것을 의미한다. 이 관계를 명확하게 나타내기 위해 지하수위 최대변동폭과 평균제곱근오차 및 최대오차와의 관계를 선형회귀식으로 도출하여 허용가능한 예측오차 기준을 제시하였다. 그리고 기존 연구들에서 제시한 Nash-Sutcliffe 효율성지수와 결정계수를 분석하여 선형회귀식에 의한 기준을 보완할 수 있는 추가적인 기준을 제시하였다. 본 연구에서 제시한 인공지능 모델에 의한 지하수위 예측결과의 적절성 판단기준은 향후 지속적으로 증가하는 인공지능 예측연구에 유용하게 사용될 수 있다.

• Journal of the Korea Institute of Building Construction
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• v.16 no.6
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• pp.487-495
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• 2016

The losses of accidents in the construction industry was significantly increased during the past decades. Therefore, the study of risk management measures in the domestic construction has become very important, and the inherent risk factors need to derive and analyze them based on the quantified method. However, most studies on the construction risk are conducted finding on the qualitative way. This study analysis the accident records from actual construction sites as a quantities study. A correlation analysis and regression analysis are adopted to identify the risk factors and develop a model. The results of this study are expected to be evolve through the accumulated effect and verification of data in the future through continuous feedback.

• Land and Housing Review
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• v.12 no.4
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• pp.93-101
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• 2021

As the number of small households (1 to 2 persons per household) in Korea gradually increases, so does the importance of housing supply policies for small households. In response to the increase in small households, the government has been continuously supplying urban housing for these households. Since housing for small households is a sales and rental business similar to apartments and general business facilities, it is important for the building owner to calculate the project's estimated construction duration during the planning stage. Review of literature found a model for estimating the duration of construction of large-scale buildings but not for small-scale buildings such as urban housing for small households. Therefore this study aimed to develop and verify a model for estimating construction duration for urban housing at the planning stage based on multiple regression analysis. Independent variables inputted into the estimation model were building site area, building gross floor area, number of below ground floors, number of above ground floors, number of buildings, and location. The modified coefficient of determination (R_a²) of the model was 0.547. The developed model resulted in a Root Mean Square Error (RMSE) of 171.26 days and a Mean Absolute Percentage Error (MAPE) of 26.53%. The developed estimation model is expected to provide reliable construction duration calculations for small-scale urban residential buildings during the planning stage of a project.

• Journal of Bio-Environment Control
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• v.32 no.2
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• pp.115-121
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• 2023

The leopard plant has the characteristic of being used for ornamental purposes when there are yellow spots on the leaves, and is widely used as a bed plant for viewing flowers. To set several indicators to predict the growth of crops with ornamental value, and to quantitatively express the relationship between the indicators are necessary. In this study, we determine a model that estimates the leaf area and the number of flower of Farfugium japonicum Kitam. using leaf length and width, and conducting a regression analysis on some regression models. As an indicator for estimating the leaf area and the number of flower, the leaf length and width of F. japonicum were measured and applied to 8 regression models. As a result of regression analysis of 8 models that estimated leaf area and the number of flower, R² values of the linear models were all higher than 0.84 and 0.80. As a result of validation, using the most reliable model among the models for estimating the leaf area and the number of flowering, R² was 0.90 and 0.82, respectively. Using a model that estimates various indicators that can be used for quality evaluation from easy-to-measure morphological factors, the evaluation of ornamental plants will be facilitated.

• Journal of the Korea Concrete Institute
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• v.16 no.2 s.80
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• pp.195-204
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• 2004

Poisson's ratio due to multiaxial creep of concrete reported by existing experimental works was controversial. Poisson's ratio calculated from measured strain is very sensitive to small experimental error. This sensitivity make it difficult to find out whether the Poisson's ratio varies with time or remain constant, and whether the Poisson's ratio has different value with stress states or not. A new approach method is needed to resolve the discrepancy and obtain reliable results. This paper presents analytical study on multiaxial creep test results. Microplane model as a new approach method is applied to optimally fitting the test data extracted from experimental studies on multiaxial creep of concrete. Double-power law is used as a model to present volumetric and deviatoric creep evolutions on a microplane. Six parameters representing the volumetric and deviatoric compliance functions are determined from regression analysis and the optimum fits accurately describe the test data. Poisson's ratio is calculated from the optimum fits and its value varies with time. Regression analysis is also performed assuming that Poisson's ratio remains constant with time. Four parameters are determined for this condition, and the error between the optimum fits and the test data is slightly larger than that for six parameter regression results. The constant Poisson's ratio with time is obtained from four parameter analysis results and the constant value can be used in practice without serious error.