• Computers and Concrete
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• 제24권4호
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• pp.295-302
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• 2019

Evolutionary algorithms based on conventional statistical methods such as regression and classification have been widely used in data mining applications. This work involves application of gene expression programming (GEP) for predicting compressive strength of fly ash geopolymer concrete, which is gaining increasing interest as an environmentally friendly alternative of Portland cement concrete. Based on 56 test results from the existing literature, a model was obtained relating the compressive strength of fly ash geopolymer concrete with the significantly influencing mix design parameters. The predictions of the model in training and validation were evaluated. The coefficient of determination ($R^2$), mean (${\mu}$) and standard deviation (${\sigma}$) were 0.89, 1.0 and 0.12 respectively, for the training set, and 0.89, 0.99 and 0.13 respectively, for the validation set. The error of prediction by the model was also evaluated and found to be very low. This indicates that the predictions of GEP model are in close agreement with the experimental results suggesting this as a promising method for compressive strength prediction of fly ash geopolymer concrete.

• 대한기계학회논문집A
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• 제30권8호
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• pp.923-930
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• 2006

A Kriging model is a sort of approximation model and used as a deterministic model of a computationally expensive analysis or simulation. Although it has various advantages, it is difficult to assess the accuracy of the approximated model. It is generally known that a mean square error (MSE) obtained from the kriging model can't calculate statistically exact error bounds contrary to a response surface method, and a cross validation is mainly used. But the cross validation also has many uncertainties. Moreover, the cross validation can't be used when a maximum error is required in the given region. For solving this problem, we first proposed a modified mean square error which can consider relative errors. Using the modified mean square error, we developed the strategy of adding a new sample to the place that the MSE has the maximum when the MSE is used for the assessment of the kriging model. Finally, we offer guidelines for the use of the MSE which is obtained from the kriging model. Four test problems show that the proposed strategy is a proper method which can assess the accuracy of the kriging model. Based on the results of four test problems, a convergence coefficient of 0.01 is recommended for an exact function approximation.

• 한국태양에너지학회 논문집
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• 제33권3호
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• pp.17-26
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• 2013

The aim of this study is to analyze the performance of a parabolic trough solar collector (PTC) for water heating and to validate the model performance. The simulated model was compared, calibrated and verified with the experimental results. RMSE (Root mean square error) was used to calibrate the convective heat transfer coefficient between the absorber pipe and the ambient air which was the main factor affecting the heat transfer associated with the PTC. The calibrated model was better fitted with the experimental model. The maximum, minimum and mean deviation between the measured and predicted water temperatures differed only $0.81^{\circ}C$, $0.09^{\circ}C$ and $0.31^{\circ}C$ respectively in the calibrated model. RMSE values were decreased from 0.5389 to 0.4910, 0.0134 to 0.0125 and R-squared was increased from 0.9955 to 0.9956 after calibration. The temperature of water was increased from $33.7^{\circ}C$ to $48^{\circ}C$ in 12hour test. The thermal efficiency of the collector was calculated to be 55%. The calibrated model showed good agreement with the experimental data for model validation.

• International Journal of Naval Architecture and Ocean Engineering
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• 제3권1호
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• pp.9-19
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• 2011

The paper describes the validation of two time domain methods to simulate the behaviour of a destroyer operating in steep, stern-quartering seas. The significance of deck-edge immersion and water on deck on the capsize risk is shown as well as the necessity to account for the wave disturbances caused by the ship. A method is described to reconstruct experimental wave trains and finally two deterministic validation cases are shown.

• International Journal of Aeronautical and Space Sciences
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• 제14권2호
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• pp.122-132
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• 2013

In this research the development of unstructured grid discretization solution techniques is presented. The purpose is to describe such a conservative discretization scheme applied for experimental validation work. The objective of this paper is to better establish the effects of mesh generation techniques on velocity fields and particle deposition patterns to determine the optimal aerodynamic characteristics. In order to achieve the objective, the mesh surface discretization approaches used the VLA prototype manufacturing tolerance zone of the outer surface. There were 3 schemes for this discretization study implementation. They are solver validation, grid convergence study and surface tolerance study. A solver validation work was implemented for the simple 2D and 3D model to get the optimum solver for the VLA model. A grid convergence study was also conducted with a different growth factor and cell spacing, the amount of mesh can be controlled. With several amount of mesh we can get the converged amount of mesh compared to experimental data. The density around surface model can be calculated by controlling the number of element in every important and sensitive surface area of the model. The solver validation work result provided the optimum solver to employ in the VLA model analysis calculation. The convergence study approach result indicated that the aerodynamic trend characteristic was captured smooth enough compared with the experimental data. During the surface tolerance scheme, it could catch the aerodynamics data of the experiment data. The discretization studies made the validation work more efficient way to achieve the purpose of this paper.

• 한국농공학회논문집
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• 제66권1호
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• pp.1-13
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• 2024

This study assessed the efficacy of improving the accuracy of reservoir water level prediction models by employing automated machine learning models and efficient cross-validation methods for time-series data. Considering the inherent complexity and non-linearity of time-series data related to reservoir water levels, we proposed an optimized approach for model selection and training. The performance of twelve models was evaluated for the Obong Reservoir in Gangneung, Gangwon Province, using the TPOT (Tree-based Pipeline Optimization Tool) and four cross-validation methods, which led to the determination of the optimal pipeline model. The pipeline model consisting of Extra Tree, Stacking Ridge Regression, and Simple Ridge Regression showed outstanding predictive performance for both training and test data, with an R² (Coefficient of determination) and NSE (Nash-Sutcliffe Efficiency) exceeding 0.93. On the other hand, for predictions of water levels 12 hours later, the pipeline model selected through time-series split cross-validation accurately captured the change pattern of time-series water level data during the test period, with an NSE exceeding 0.99. The methodology proposed in this study is expected to greatly contribute to the efficient generation of reservoir water level predictions in regions with high rainfall variability.

• 시스템엔지니어링워크숍
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• 통권1호
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• pp.9-14
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• 2003

The paper aims at presenting a systematic approach process and a method of requirement validation and system verification. Validation is applied during concept development to ensure conceptual validity, requirements validity, and design validity. Verification work is applied subsequent to the design work on test articles and early production items to produce evidence that the design solutions do, in fact, satisfy th requirements. In this paper, we present a requirements validation model and a system verification model. This models are applied to the development of TTX(Tilting Train Express)system with systems engineering tool, CORE.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.995-1004
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• 2007

In this paper, we analyse online word-of-mouth and Korean box-office sales data based on kernel regression method. To do this, we consider the regression model with mixed-data and apply the least square cross-validation method proposed by Li and Racine (2004) to the model. We found the box-office sales can be explained by volume of online word-of-mouth and the characteristics of the movies.

• 인터넷정보학회논문지
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• 제17권5호
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• pp.131-139
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• 2016

This paper presents a workflow validation method for data-intensive graphical workflow models using real-time workflow tracing mode on data-intensive workflow designer. In order to model and validate workflows, we try to divide as modes have editable mode and tracing mode on data-intensive workflow designer. We could design data-intensive workflow using drag and drop in editable-mode, otherwise we could not design but view and trace workflow model in tracing mode. We would like to focus on tracing-mode for workflow validation, and describe how to use workflow tracing on data-intensive workflow model designer. Especially, it is support data centered operation about control logics and exchange variables on workflow runtime for workflow tracing.

• 한국항공운항학회지
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• 제14권2호
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• pp.9-16
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• 2006

FAA AC120-40B Level D flight dynamics model for T-50 Full Mission Trainer was successfully developed. Since AC120-40B Level D requires the quantitative validation tests for simulation model compared with flight test data, T-50 flight test data for each validation test item was gathered, and also automatic test environments which include AFT (Automatic Fidelity Tester) and STA (Simulation Test Analyzer) were developed. The final test results after the iterative test-tuning processes were all within the tolerances specified in AC120-40B Level D. Qualification Test Guide, QTG contains the detail test processes and results.