• 대한산업공학회지
• /
• 제27권1호
• /
• pp.47-53
• /
• 2001

In this paper, we compare the classification performances of both ensemble and clustering algorithms (Data Bagging, Variable Selection Bagging, Parameter Combining, Clustering) to logistic regression in consideration of various characteristics of input data. Four factors used to simulate the logistic model are (1) correlation among input variables (2) variance of observation (3) training data size and (4) input-output function. In view of the unknown relationship between input and output function, we use a Taguchi design to improve the practicality of our study results by letting it as a noise factor. Experimental study results indicate the following: When the level of the variance is medium, Bagging & Parameter Combining performs worse than Logistic Regression, Variable Selection Bagging and Clustering. However, classification performances of Logistic Regression, Variable Selection Bagging, Bagging and Clustering are not significantly different when the variance of input data is either small or large. When there is strong correlation in input variables, Variable Selection Bagging outperforms both Logistic Regression and Parameter combining. In general, Parameter Combining algorithm appears to be the worst at our disappointment.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
• /
• pp.664-667
• /
• 1997

For higher component density per chip, it is necessary to identify and control the semiconductor manufacturing process more stringently. Recently, neural networks have been identified as one of the most promising techniques for modeling and control of complicated processes such as plasma etching process. Since wafer states after each run using identical recipe may differ from each other, conventional neural network models utilizing input factors only cannot represent the actual state of process and equipment. In this paper, in addition to the input factors of the recipe, real-time tool data are utilized for modeling of 64M DRAM s-poly plasma etching process to reflect the actual state of process and equipment. For real-time tool data, we collect optical emission spectroscopy (OES) data. Through principal component analysis (PCA), we extract principal components from entire OES data. And then these principal components are included to input parameters of neural network model. Finally neural network model is trained using feed forward error back propagation (FFEBP) algorithm. As a results, simulation results exhibit good wafer state prediction capability after plasma etching process.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 2010년도 하계학술대회 논문집
• /
• pp.327-327
• /
• 2010

In this paper, an investigation of factors affecting piezoelectric transformers is presented by ATILA software. These transformers are multi-layer piezoelectric transformers in square shape $28\;{\times}\;28\;mm$ and operate in first vibration mode for step-down function. The piezoelectric transformers were modeled in 3D-dimension and analyzed using finite element method in ATILA software, a popular software in piezoelectric analysis. Modal and harmonic modules were used in this process. Effective factors to the properties of piezoelectric transformers including different input electrode patterns, directions of polarization, sizes of connective comer, number of layers were examined on the simulated model using input voltage of 20 V and load resistance of $100\;{\Omega}$. Moreover, thermal analysis was also obtained with conditions of input voltage of 5 V and no-load.

• Steel and Composite Structures
• /
• 제34권1호
• /
• pp.155-170
• /
• 2020

Different parameters potentially affect the properties of corroded reinforced concrete beams. However, the high number of these parameters and their dependence cause that the effectiveness of the parameters could not be simply identified. In this study, an adaptive neuro-fuzzy inference system (ANFIS) was employed to determine the most influencing parameters on the properties of the corrosion-damaged reinforced concrete beams. 207 ANFIS models were developed to analyze the collected data from 107 reinforced concrete (RC) beams. The impact of 23 input parameters on nine output factors was investigated. The results of the paper showed the order of influence of each input parameter on the outputs and revealed that the input parameters regarding the uncorroded properties of concrete beams are the most influencing factors on the corresponding corroded properties of the beams.

• 유통과학연구
• /
• 제19권7호
• /
• pp.29-39
• /
• 2021

Purpose: As China experienced a crisis due to Covid-19, the global supply chain collapsed and affected the world. Therefore, it is time for a change in port operational efficiency, increasing in importance with changes in the global supply chain. This study analyzed Shanghai Port's efficiency, the world's largest port and representative hub port in Northeast Asia, by looking at the relationship between facility factors and cargo throughput to present hub port development's timely implications. Research design, data and methodology: This study applied the Charnes, Cooper, and Rhodes (CCR) and Banker, Chames, and Cooper (BCC) models of the data development analysis (DEA) to construct an analysis from the input-oriented and output-oriented perspectives. Results: As a result, Yidong Container Terminal can be considered the most optimized in facilities and operation processes. Yidong and Shengdong Container Terminal should maintain current operating levels, while Pudong Container Terminal should review facility investments. Also, Zhendong, Huong, Mingdong, and Guandong Container Terminal should be reviewed to increase cargo throughput or to adjust current input variables in the current state. Conclusions: Therefore, the utilization of the container terminal input variables should be reviewed, and the factors of inefficiency should be improved. Moreover, the strategic focus of container terminal operations should be on increasing annual cargo throughput.

• 한국환경보건학회지
• /
• 제48권5호
• /
• pp.266-271
• /
• 2022

Background: The selection of distributions of input parameters is an important component in probabilistic exposure assessment. Goodness-of-fit (GOF) methods are used to determine the distribution of exposure factors. However, there are no clear guidelines for choosing an appropriate GOF method. Objectives: The outcomes of probabilistic consumer exposure assessment were compared by using five different GOF methods for the selection of input distributions: chi-squared test, Kolmogorov-Smirnov test (K-S), Anderson-Darling test (A-D), Akaike information criterion (AIC) and Bayesian information criterion (BIC). Methods: Individual exposures were estimated based on product usage factor combinations from 10,000 respondents. The distribution of individual exposure was considered as the true value of population exposures. Results: Among the five GOF methods, probabilistic exposure distributions using the A-D and K-S methods were similar to individual exposure estimations. Comparing the 95th percentiles of the probabilistic distributions and the individual estimations for 10 CPs, there were 0.73 to 1.92 times differences for the A-D method, and 0.73 to 1.60 times differences (excluding tire-shine spray) for the K-S method. Conclusions: There were significant differences in exposure assessment results among the selection of the GOF methods. Therefore, the GOF methods for probabilistic consumer exposure assessment should be carefully selected.

• Earthquakes and Structures
• /
• 제27권1호
• /
• pp.41-55
• /
• 2024

There are obvious differences between the characteristics of offshore ground motion and onshore ground motion in current studies, and factors such as water layer and site conditions have great influence on the characteristics of offshore ground motion. In addition, unlike seismic response analysis of offshore superstructures such as sea-crossing bridges, tunnels are affected by offshore soil constraints, so it is necessary to consider the dynamic interaction between structure and offshore soil layer. Therefore, a seismic response analysis model considering the seawater, soil layer and tunnel structure coupling is established. Firstly, the measured offshore and different soil layers onshore ground records are input respectively, and the difference of seismic response under different types of ground motions is analyzed. Then, the models of different site conditions were input into the measured onshore bedrock strong ground motion records to study the influence of seawater layer and silt soft soil layer on the seabed and tunnel structure. The results show that the overall seismic response between the seabed and the tunnel structure is more significant when the offshore ground motion is input. The seawater layer can suppression the vertical seismic response of seabed and tunnel structure, while the slit soft soil layer can amplify the horizontal seismic response. The results will help to promote seismic wave selection of marine structures and provide reference for improving the accuracy of seismic design of immersed tunnels.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
• /
• pp.1799-1802
• /
• 2003

This paper has been studied a Adaptive feature-factors based fingerprints recognition in many biometrics. we study preprocessing and matching method of fingerprints image in various circumstances by using optical fingerprint input device. The Fingerprint Recognition Technology had many development until now. But, There is yet many point which the accuracy improves with operation speed in the side. First of all we study fingerprint classification to reduce existing preprocessing step and then extract a Feature-factors with direction information in fingerprint image. Also in the paper, we consider minimization of noise for effective fingerprint recognition system.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2004년도 추계학술대회
• /
• pp.1312-1316
• /
• 2004

The Stirling refrigerators have been widely used for the cooling of the infrared detector and HTS to the cryogenic temperature. The Stirling refrigerator with the rotary compressor are applicable to the cooling device for the compact mobile thermal imaging system, because the refrigerators have the compact structure and light weight. The typical performance factors of the Stirling refrigerator are the cool-down time, cooling capacity at the desired temperature and the input power. And the above performance factors are depends on the thermal insulation characteristics of the Dewar. In this study, the steady thermal load of the Dewar and the performance of the Stirling refrigerator were measured. The results show the dependency of the input power and the charging pressure on the performance of the refrigerator.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2006년도 추계학술대회논문집
• /
• pp.25-29
• /
• 2006

Noise map presents new alternatives of noise reduction counter measure and becomes important tool for making environmental policy. Many input factors such as road conditions, number of vehicles, speeds of vehicles are used for noise prediction of the noise map. However, results of noise prediction make difference depending on the values of the input factors. In this study, effect of measurement method for vehicle speeds all the prediction results of the noise map.