• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.785-799
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• 2018

With the development of renewable energy sector, the importance of solar energy is continuously increasing. Solar radiation forecasting is essential to accurately solar power generation forecasting. In this paper, we used time series models (ARIMA, ARIMAX, seasonal ARIMA, seasonal ARIMAX, ARIMA GARCH, ARIMAX-GARCH, seasonal ARIMA-GARCH, seasonal ARIMAX-GARCH). We compared the performance of the models using mean absolute error and root mean square error. According to the performance of the models without exogenous variables, the Seasonal ARIMA-GARCH model showed better performance model considering the problem of heteroscedasticity. However, when the exogenous variables were considered, the ARIMAX model showed the best forecasting accuracy.

• Women's Health Nursing
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• v.25 no.1
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• pp.31-45
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• 2019

Purpose: This study was designed to develop a valid and reliable scale for the evaluation of preconception health behavior in women preparing for pregnancy. Methods: The initial strategy included a literature review, interviews, and construction of a conceptual framework. The preliminary items were evaluated twice for content validity by experts, and modified two preliminary investigations. Participants in the 2 main investigations and the confirmation investigation were tested for reliability and validity of the preliminary scale in women preparing for pregnancy. The data were analyzed for different items exploratory and confirmatory factors. Results: The 5-point Likert scale consisted of 6 factors and 27 items. The 6-factors included 'hazardous substance factor,' 'medical management factor,' 'rest and sleep factor,' 'stress management factor,' 'information acquisition factor,' and 'resource preparation factor.' Goodness of fit of the final research model was very appropriate and based on the following measures: Q=1.98, comparative fit index=.91, Tucker-lewis index=.89, standardized root mean square residual=.07, and root mean square error of approximation=.07. The criterion validity was .64. The reliability coefficient was .92 and the test-retest reliability was .61. Conclusion: The study findings indicate that the scale can be used for the development of nursing interventions to promote preconception health behavior in women preparing for pregnancy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.837-839
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• 2014

In radar systems, information of three-dimensional (3D) trajectory is necessary for tracking targets. The information of 3D trajectory for a 3D radar can be obtained by estimating the azimuth angle, the elevation angle, and the distance. The estimated information of the angles and the distance has errors according to received signals. Since these errors affect performances of 3D radar systems, performance analysis of 3D radar for the angles and the distance errors is required. In this paper, the performance of 3D radar systems is analyzed by root mean square error (RMSE) between true trajectory information and the estimated trajectory information according to the angles and the distance errors.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.671-683
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• 2021

Power allocation is a technique that evenly allocates samples for each stratum, although the overall efficiency of the allocation is less than that of optimal allocation, and it is often used as a square root proportional allocation in real survey. Also, considering the non-response that occurs in real survey, a larger sample size is used than that in the theoretical formula. In this study, in determining the sample size for each stratum, we study the new methods of allocating by adding information on the response rate per each stratum to power allocation method. The proposed allocation methods are compare with proportional, optimal, and square root proportional allocation in simulation. In addition, the comparison with the proportional and optimal allocation to which the response rate was added is examined through simulation. As a result, we examine the advantages and disadvantages of the allocation methods.

• Journal of Environmental Science International
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• v.31 no.7
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• pp.555-567
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• 2022

With the introduction of the tele-monitoring system (TMS) in South Korea, monitoring of the concentration of pollutants discharged from nationwide water quality TMS attachments is possible. In addition, the Ministry of Environment is implementing a smart sewage system program that combines ICT technology with wastewater treatment plants. Thus, many institutions are adopting the automatic operation technique which uses process operation factors and TMS data of sewage treatment plants. As a part of the preliminary study, a multilayer perceptron (MLP) analysis method was applied to TMS data to identify predictability degree. TMS data were designated as independent variables, and each pollutant was considered as an independent variables. To verify the validity of the prediction, root mean square error analysis was conducted. TMS data from two public sewage treatment plants in Chungnam were used. The values of RMSE in SS, T-N, and COD predictions (excluding T-P) in treatment plant A showed an error range of 10%, and in the case of treatment plant B, all items showed an error exceeding 20%. If the total amount of data used MLP analysis increases, the predictability of MLP analysis is expected to increase further.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4179-4188
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• 2021

This study identifies efficient earthquake intensity measures (IMs) for seismic performances and fragility evaluations of the reactor containment building (RCB) in the advanced power reactor 1400 (APR1400) nuclear power plant (NPP). The computational model of RCB is constructed using the beam-truss model (BTM) for nonlinear analyses. A total of 90 ground motion records and 20 different IMs are employed for numerical analyses. A series of nonlinear time-history analyses are performed to monitor maximum floor displacements and accelerations of RCB. Then, probabilistic seismic demand models of RCB are developed for each IM. Statistical parameters including coefficient of determination (R²), dispersion (i.e. standard deviation), practicality, and proficiency are calculated to recognize strongly correlated IMs with the seismic performance of the NPP structure. The numerical results show that the optimal IMs are spectral acceleration, spectral velocity, spectral displacement at the fundamental period, acceleration spectrum intensity, effective peak acceleration, peak ground acceleration, A95, and sustained maximum acceleration. Moreover, weakly related IMs to the seismic performance of RCB are peak ground displacement, root-mean-square of displacement, specific energy density, root-mean-square of velocity, peak ground velocity, Housner intensity, velocity spectrum intensity, and sustained maximum velocity. Finally, a set of fragility curves of RCB are developed for optimal IMs.

• Advances in materials Research
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• v.11 no.1
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• pp.75-90
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• 2022

In this paper, functionality of soft computing algorithms such as Group method of data handling (GMDH), Random forest (RF), Random tree (RT), Linear regression (LR), M5P, and artificial neural network (ANN) have been looked out to predict the compressive strength of concrete mixed with marble powder. Assessment of result suggests that, the overall performance of ANN based model gives preferable results over the different applied algorithms for the estimate of compressive strength of concrete. The results of coefficient of correlation were maximum in ANN model (0.9139) accompanied through RT with coefficient of correlation (CC) value 0.8241 and minimum root mean square error (RMSE) value of ANN (4.5611) followed by RT with RMSE (5.4246). Similarly, other evaluating parameters like, Willmott's index and Nash-sutcliffe coefficient value of ANN was 0.9458 and 0.7502 followed by RT model (0.8763 and 0.6628). The end result showed that, for both subsets i.e., training and testing subset, ANN has the potential to estimate the compressive strength of concrete. Also, the results of sensitivity suggest that the water-cement ratio has a massive impact in estimating the compressive strength of concrete with marble powder with ANN based model in evaluation with the different parameters for this data set.

• Geomechanics and Engineering
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• v.30 no.5
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• pp.437-448
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• 2022

Alluvial soil is challenging to work with due to its high compressibility. Thus, consolidation settlement of this type of soil should be accurately estimated. Accurate estimation of the consolidation settlement of alluvial soil requires accurate prediction of compressibility parameters. Geotechnical engineers usually use empirical correlations to estimate these compressibility parameters. However, no attempts have been made to develop correlations to estimate compressibility parameters of alluvial soil. Thus, this paper aims to develop new models to predict the compression and recompression indices (Cc and Cr) of alluvial soils. As part of the study, geotechnical laboratory tests have been conducted on large number of undisturbed samples of local alluvial soil. The obtained results from these tests in addition to available results from the literature from different parts in the world have been compiled to form the database of this study. This database is then employed to examine the accuracy of the available empirical correlations of the compressibility parameters and to develop the new models to estimate the compressibility parameters using the nonlinear regression analysis. The accuracy of the new models has been accessed using mean absolute error, root mean square error, mean, percentage of predictions with error range of ±20%, percentage of predictions with error range of ±30%, and coefficient of determination. It was found that the new models outperform the available correlations. Thus, these models can be used by geotechnical engineers with more confidence to predict Cc and Cr.

• Steel and Composite Structures
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• v.46 no.4
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• pp.577-589
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• 2023

In this study, on-site testing was carried out to investigate the vibration performance of a cold-formed thin-walled steel floor system. Ambient vibration, walking excitation (single and double persons), and impulsive excitation (heel-drop and jumping) were considered to capture the primary vibration parameters (natural frequencies, damping ratios, and mode shapes) and vertical acceleration response. Meanwhile, to discuss the influence of cement fiberboard on structural vibration, the primary vibration parameters were compared between the systems with and without the installation of cement fiberboard. Based on the experimental analysis, the cold-formed thin-walled steel floor possesses high frequency (> 10 Hz) and damping (> 2%); the installed cement fiberboard mainly increases the mass of floor system without effectively increasing the floor stiffness and may reduce the effects of primary vibration parameters on acceleration response; and the human-structure interaction should be considered when analyzing the vibration serviceability. The comparison of the experimental results with those in the AISC Design Guide indicates that the cold-formed thin-walled steel floor exhibits acceptable vibration serviceability. A crest factor 𝛽_rp (ratio of peak to root-mean-square accelerations) is proposed to determine the root-mean-square acceleration for convenience.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.117-124
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• 2023

In the machine vision inspection equipment, diameter measurement is important process in inspection of cylindrical object. However, machine vision inspection equipment requires complex algorithm processing such as camera distortion correction and perspective distortion correction, and the increase in processing time and cost required for precise diameter measurement. In this paper, we proposed the algorithm for diameter measurement of cylindrical object using the laser displacement sensor. In order to fit circle for given four input outer points, grid search algorithms using root-mean-square error and mean-absolute error are applied and compared. To solve the limitations of the grid search algorithm, we finally apply the singular-value-decomposition based circle fitting algorithm. In order to compare the performance of the algorithms, we generated the pseudo data of the outer points of the cylindrical object and applied each algorithm. As a result of the experiment, the grid search using root-mean-square error confirmed stable measurement results, but it was confirmed that real-time processing was difficult as the execution time was 10.8059 second. The execution time of mean-absolute error algorithm was greatly improved as 0.3639 second, but there was no weight according to the distance, so the result of algorithm is abnormal. On the other hand, the singular-value-decomposition method was not affected by the grid and could not only obtain precise detection results, but also confirmed a very good execution time of 0.6 millisecond.