• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.21-27
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• 2011

When execute runoff forecasting, can not remove perfectly uncertainty of forecasting results. But, reduce uncertainty by various techniques analysis. This study applied various forecasting techniques for runoff prediction's accuracy elevation in Gongju basin. statics techniques is ESP, Period Average & Moving average, Exponential Smoothing, Winters, Auto regressive moving average process. Authoritativeness estimation with results of runoff forecasting by each techniques used MAE (Mean Absolute Error), RMSE (Root Mean Squared Error), RRMSE (Relative Root Mean Squared Error), Mean Absolute Percentage Error (MAPE), TIC (Theil Inequality Coefficient). Result that use MAE, RMSE, RRMSE, MAPE, TIC and confirm improvement effect of runoff forecasting, ESP techniques than the others displayed the best result.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.103-109
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• 2018

Purpose: This study has been conducted to develop a potato yield monitoring system, consisting of a segmentation algorithm to detect potatoes scattered on a soil surface and a counting system to count the number of potatoes and convert the data from two-dimensional images to masses. Methods: First, a segmentation algorithm was developed using top-hat filtering and processing a series of images, and its performance was evaluated in a stationary condition. Second, a counting system was developed to count the number of potatoes in a moving condition and calculate the mass of each using a mass estimation equation, where the volume of a potato was obtained from its two-dimensional image, and the potato density and a correction factor were obtained experimentally. Experiments were conducted to segment potatoes on a soil surface for different potato sizes. The counting system was tested 10 times for 20 randomly selected potatoes in a simulated field condition. Furthermore, the estimated total mass of the potatoes was compared with their actual mass. Results: For a $640{\times}480$ image size, it took 0.04 s for the segmentation algorithm to process one frame. The root mean squared deviation (RMSD) and average percentage error for the measured mass of potatoes using this counting system were 12.65 g and 7.13%, respectively, when the camera was stationary. The system performance while moving was the best in L1 (0.313 m/s), where the RMSD and percentage error were 6.92 g and 7.79%, respectively. For 20 newly prepared potatoes and 10 replication measurements, the counting system exhibited a percentage error in the mass estimation ranging from 10.17-13.24%. Conclusions: At a travel speed of 0.313 m/s, the average percentage error and standard deviation of the mass measurement using the counting system were 12.03% and 1.04%, respectively.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1448-1456
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• 2022

This paper studies a model to diagnose efficiency reduction of inverter using Multilayer Perceptron(MLP). In this study, two inverter data which started operation at different day was used. A Multilayer Perceptron model was made to predict photovoltaic power data of the latest inverter. As a result of the model's performance test, the Mean Absolute Percentage Error(MAPE) was 4.1034. The verified model was applied to one-year-old and two-year-old data after old inverter starting operation. The predictive power of one-year-old inverter was larger than the observed power by 724.9243 on average. And two-year-old inverter's predictive value was larger than the observed power by 836.4616 on average. The prediction error of two-year-old inverter rose 111.5572 on a year. This error is 0.4% of the total capacity. It was proved that the error is meaningful difference by t-test. The error is predicted value minus actual value. Which means that PV system actually generated less than prediction. Therefore, increasing error is decreasing conversion efficiency of inverter. Finally, conversion efficiency of the inverter decreased by 0.4% over a year using this model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.10-20
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• 2012

This study shows how to estimate AADT(Annual Average Daily Traffic) on temporary count data using new grouping method. This study deals with clustering permanent traffic counts using monthly adjustment factor, daily adjustment factor and a percentage of hourly volume. This study uses a percentage of hourly volume comparing with other studies. Cluster analysis is used and 5 groups is suitable. First, make average of monthly adjustment factor, average of daily adjustment factor, a percentage of hourly volume for each group. Next estimate AADT using 24 hour volume(not holiday) and two adjustment factors. Goodness of fit test is used to find what groups are applicable. MAPE(Mean Absolute Percentage Error) is 8.7% in this method. It is under 1.5% comparing with other method(using adjustment factors in same section). This method is better than other studies because it can apply all temporary counts data.

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.385-393
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• 2022

In this paper, we consider univariate time series models that are well known in the field of forecasting and we study on forecasting performance for their simple combinations. The univariate time series models include exponential smoothing methods and ARIMA (autoregressive integrated moving average) models, their extended models, and non-seasonal and seasonal random walk models, which is frequently used as benchmark models for forecasting. The median and mean are simply used for the combination method, and the data set used for performance evaluation is M3-competition data composed of 3,003 various time series data. As results of evaluating the performance by sMAPE (symmetric mean absolute percentage error) and MASE (mean absolute scaled error), we assure that the simple combinations of the univariate models perform very well in the M3-competition dataset.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1041-1045
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• 2010

Short-term electric load forecasting of power systems is essential for the power system stability and the efficient power system operation. An accurate load forecasting scheme improves the power system security and saves some economic losses in power system operations. Due to scarcity of the historical same type of holiday load data, most big electric load forecasting errors occur on load forecasting for the holidays. The fuzzy linear regression model has showed good accuracy for the load forecasting of the holidays. However, it is not good enough to forecast the load of the election day. The concept of the load variation rate for the load forecasting of the election day is introduced. The proposed algorithm shows its good accuracy in that the average percentage error for the short-term 24 hourly loads forecasting of the election days is 2.27%. The accuracy of the proposed 24 hourly loads forecasting of the election days is compared with the fuzzy linear regression method. The proposed method gives much better forecasting accuracy with overall average error of 2.27%, which improved about average error of 2% as compared to the fuzzy linear regression method.

• Journal of the Korea Safety Management & Science
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• v.17 no.3
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• pp.133-141
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• 2015

This study tried to identify the problems associated with the posture to be analyzed and tried to suggest guidelines for MSDs(Musculoskeletal Disorders) evaluation based on working posture. A total of 50 jobs from 3 different types of industries(electronics, hospitals, automobiles) were used for MSDs evaluation study which was done by 6 observers. Two indexes were applied to identify the problem in this study which were percentage of agreement and counter-time-error rate. Specifically, 'counter-time-error rate' represented a degree of consistency in terms of selecting the posture to be analyzed time after time. Main results of the study were as follows; 1) The average percentage of agreement for representative posture for whole body was relatively higher than that for representative postures for individual body parts, 2) The counter-time-error rate(%) has been reduced as the evaluation process has repeated for the same job. 3) The counter-time-error rate(%) for electronics, hospitals, and automobiles were 63.4%, 61.2%, and 67.3% respectively. 4) The counter-time-error rate(%) for the job with the work cycle of 0.5 to 2 minutes were lower than that of the jobs with the work cycles less than 0.5 minute or greater than 2 minute. 5) The work cycles and the number of trials had significant effects on counter-time-error rate while the types of industries did not have significant effects on counter-time-error rate. Some guidelines could be prepared from the results of the study. Probably, there should have an extension in terms of form and matter for this study in order to have more practical output.

• Journal of the Korean Society of Radiology
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• v.12 no.5
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• pp.651-658
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• 2018

A foot pedal switch in the diagnosis x-ray radiography system has been researched to improve radiologic technologist works and patient satisfaction. The switch has been installed in the diagnosis x-ray radiography system used in domestic clinics. Quantitative evaluation has been conducted by measuring the exposure dose reproducibility test, tube voltage, mAs, and percentage average error. Qualitative evaluation has been conducted by analysis of the radiologic technologists questionnaire. In the quantitative evaluation for the use of the foot pedal switch, the coefficient of variation was less than 0.05 in the exposure dose reproducibility test. In the mAs test, percentage average error of ${\pm}20%$ was measured. There was no problem raised since it meets the all inspection standards of the diagnosis x-ray generator. In the qualitative evaluation, most of the opinions are that it has a clinical value for the foot pedal switch in the diagnosis x-ray radiography system. Therefore, developing the foot pedal switch for the diagnosis x-ray radiography system can improve effectively the rapidity and accuracy of the radiologic technologist work. In addition, it is effective in decreasing the x-ray exposure of patients and increasing satisfaction for the medical service due to reduction of retaking x-ray.

• Journal of the Korean Society of Radiology
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• v.14 no.2
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• pp.139-148
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• 2020

The purpose of this study is to propose a method to optimize the performance of Digital Radiography (DR) by analyzing the effect of exposure time change on the stability of radiation output and image quality. The experimental method was used to change the exposure time to 50 msec, 100 msec, 200 msec, and 400 msec so that the Percentage Average Error (PAE), Time-to-Radiation Dose Curve, Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR) and theses analysis were performed to evaluate the normal operation of parameters, radiation output and image quality. As a result, all the parameters used in the experiment showed the Percentage Average Error in the normal range, and the shorter the exposure time, the stability of radiation output and image quality decrease. In conclusion, it was found that the performance of Digital Radiography can be optimized when stable radiation output and image quality are applied by applying 100 msec ~ 200 msec exposure time.

• Journal of the Korean Society of Radiology
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• v.14 no.4
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• pp.375-383
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• 2020

This study aimed to propose a methodology for quantitatively analyzing problems resulting from the performance and combination of the ionization chamber when using an automatic exposure control (AEC) and to optimize the performance of the digital radiography (DR). In the experimental method, the X-ray quality of the parameters used for the examination of the abdomen and pelvis was evaluated by percentage average error (PAE) and half value layer (HVL). Then, the stability of the radiation output and the image quality were analyzed by calculating the entrance surface dose (ESD) and entropy when the three ionization chambers were combined. As a result, all of the X-ray quality of the digital radiography used in the experiment showed a percentage average error and a half value layer in the normal range. The entrance surface dose increased in proportion to the combination of chambers, and entropy increased in proportion to the combination of ionization chambers except when three chambers were combined. In conclusion, analysis using entrance surface dose and entropy was found to be a useful method for evaluating the performance and combination problems of the ionization chamber, and the optimal performance of the digital radiography can be maintained when two or less ionization chambers are combined.