• 한국항만경제학회지
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• 제20권2호
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• pp.151-167
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• 2004

Traditional traffic forecast has employed regression analysis or time-series analysis based on past trends of explanatory variables. However, not existing but planned port facilities do not have historical data for traffic estimation. Consequently, arbitrary traffic allocation has been subject to researcher's intuition. In this paper, container throughput at New Incheon Outer-South Port will be estimated using stated preference(SP) and sample enumeration methodology on the basis of survey data about the choice behaviors of port users in a theoretical situation. In the SP survey, shippers, freight forwarders and carriers were required to answer a choice between two alternative ports: Busan and Incheon. Although total 27 scenarios of questionnaires were constructed with 3 levels of 3 explanatory variables, each interviewee was asked to answer for just 9 scenarios chosen at random. A binary choice logit model was applied to the survey data. The elasticity of travel time is estimated to be very high, implying that building New Incheon Outer-South Port could be effective in relieving the congestion of the Kyungin corridor. The analysis result shows that increasing service level at Incheon Port would bring in the substantial diversion of container cargo in the Capital region to Incheon Port from Busan Port.

• 한국수학사학회지
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• 제30권4호
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• pp.247-258
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• 2017

The goal of this essay is to examine metaphors for mathematics and to discuss philosophical problems related to them. Two metaphors for mathematics are well known. One is a tree and the other is a building. The former was proposed by Pasch, and the latter by Hilbert. The difference between these metaphors comes from different philosophies. Pasch's philosophy is a combination of empiricism and deductivism, and Hilbert's is formalism whose final task is to prove the consistency of mathematics. In this essay, I try to combine two metaphors from the standpoint that 'mathematics is a part of the ecosystem of science', because each of them is not good enough to reflect the holistic mathematics. In order to understand mathematics holistically, I suggest the criteria of the desirable philosophy of mathematics. The criteria consists of three categories: philosophy, history, and practice. According to the criteria, I argue that it is necessary to pay attention to Pasch's philosophy of mathematics as having more explanatory power than Hilbert's, though formalism is the dominant paradigm of modern mathematics. The reason why Pasch's philosophy is more explanatory is that it contains empirical nature. Modern philosophy of mathematics also tends to emphasize the empirical nature, and the synthesis of forms with contents agrees with the ecological analogy for mathematics.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.177-180
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• 2005

Three dimensional shaded images are standard visualization method for CAD models on the computer screen. Therefore, much of the effort in the visualization of CAD models has been focused on how conveniently and realistically CAD models can be displayed on the screen. However, shaded 3D CAD data images captured from the screen may not be suitable for some application areas. Technical document, either in the paper or electronic form, can more clearly describe the shape and annotate parts of the model by using projected 2D line drawing format viewed from a user defined view direction. This paper describes an efficient method for generating such a 2D line drawing data in the vector format. The algorithm is composed of silhouette line detection, hidden line removal and cleaning processes.

• 대한원격탐사학회지
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• 제33권4호
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• pp.445-454
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• 2017

The performance of spatial downscaling models depends on the quality of input coarse scale products. Thus, the impact of intrinsic errors contained in coarse scale satellite products on predictive performance should be properly assessed in parallel with the development of advanced downscaling models. Such an assessment is the main objective of this paper. Based on a synthetic satellite precipitation product at a coarse scale generated from rain gauge data, two synthetic precipitation products with different amounts of error were generated and used as inputs for spatial downscaling. Geographically weighted regression, which typically has very high explanatory power, was selected as the trend component estimation model, and area-to-point kriging was applied for residual correction in the spatial downscaling experiment. When errors in the coarse scale product were greater, the trend component estimates were much more susceptible to errors. But residual correction could reduce the impact of the erroneous trend component estimates, which improved the predictive performance. However, residual correction could not improve predictive performance significantly when substantial errors were contained in the input coarse scale data. Therefore, the development of advanced spatial downscaling models should be focused on correction of intrinsic errors in the coarse scale satellite product if a priori error information could be available, rather than on the application of advanced regression models with high explanatory power.

• Child Health Nursing Research
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• 제25권3호
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• pp.245-254
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• 2019

Purpose: The purpose of this study was to obtain research-based evidence on the relationships among general characteristics, family strength, self-control, and happiness among late school-aged children using a correlational research design. Methods: The participants were 172 fifth- and sixth-grade students from two public elementary schools. Data were collected by employing structured questionnaires, including the Korean Family Strengths Scale for Strengthening Family II, a self-control scale, and a happiness scale. Data analysis was conducted using SPSS version 23.0. Results: The level of happiness of late school-aged students showed significant correlations with family strength (r=.78, p<.001), and self-control (r=.59, p<.001). Family strength had a significant positive correlation with self-control (r=.55, p<.001). The factors with a significant impact on participants' happiness were family strength (${\beta}=.63$, p<.001), self-control (${\beta}=.21$, p<.001), exercise frequency, and self-perceived health. The total explanatory power of the model was 69%, and the explanatory power of family strength for the level of happiness was 61%, showing that the family strength was the most important factor that promoted happiness in late school-aged students. Conclusion: These findings imply that improving family strength is an important aspect of promoting happiness among late school-aged children. Interventions to strengthen late school-aged children's self-control are also necessary.

• 한국안전학회지
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• 제37권4호
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• pp.80-91
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• 2022

The purpose of this study is to contribute to strengthening the response of local governments to the emergence of new infectious diseases by identifying the urban characteristics affecting their spread. To this end, the urban characteristics influencing the spread of infectious diseases were identified from previous studies. Moreover, the variations in the impact of urban characteristics that affected the number of confirmed COVID-19 patients was spatially analyzed using geographically weighted regression (GWR). The analysis indicated that the explanatory power of the GWR was approximately 12.4% higher than that of the ordinary least squares method. Moreover, the explanatory power of the model in the northern regions, such as Seoul, Gyeonggi, and Gangwon, was particularly high, indicating that the urban characteristics affecting the spread of COVID-19 vary by region. The results of this study can be used as a basis for suggesting the formulation of customized policies reflecting the characteristics of each local government rather than a uniform spread reduction policy.

• Communications for Statistical Applications and Methods
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• 제20권6호
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• pp.491-498
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• 2013

We consider support vector machines(SVM) to predict Y with p numerical variables $X_1$, ${\ldots}$, $X_p$. This paper aims to build a biplot of p explanatory variables, in which the first dimension indicates the direction of SVM classification and/or regression fits. We use the geometric scheme of kernel principal component analysis adapted to map n observations on the two-dimensional projection plane of which one axis is determined by a SVM model a priori.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권5호
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• pp.1414-1430
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• 2022

Due to the Internet of Things popularity, many agricultural data are collected by sensors automatically. The abundance of agricultural data makes precise prediction of rice yield possible. Because the climate factors have an essential effect on the rice yield, we considered the climate factors in the prediction model. Accordingly, this paper proposes a machine learning model for rice yield prediction in Taiwan, including the genetic algorithm and support vector regression model. The dataset of this study includes the meteorological data from the Central Weather Bureau and rice yield of Taiwan from 2003 to 2019. The experimental results show the performance of the proposed model is nearly 30% better than MARS, RF, ANN, and SVR models. The most important climate factors affecting the rice yield are the total sunshine hours, the number of rainfall days, and the temperature.The proposed model also offers three advantages: (a) the proposed model can be used in different geographical regions with high prediction accuracies; (b) the proposed model has a high explanatory ability because it could select the important climate factors which affect rice yield; (c) the proposed model is more suitable for predicting rice yield because it provides higher reliability and stability for predicting. The proposed model can assist the government in making sustainable agricultural policies.

• 대한수학회논문집
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• 제31권1호
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• pp.185-198
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• 2016

Regression analysis is an analyzing method of regression model to explain the statistical relationship between explanatory variable and response variables. This paper propose a fuzzy regression analysis applying Theils method which is not sensitive to outliers. This method use medians of rate of increment based on randomly chosen pairs of each components of ${\alpha}$-level sets of fuzzy data in order to estimate the coefficients of fuzzy regression model. An example and two simulation results are given to show fuzzy Theils estimator is more robust than the fuzzy least squares estimator.

• Journal of the Korean Data and Information Science Society
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• 제21권1호
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• pp.1-9
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• 2010

본 논문은 분할구 실험에서 반복측정 요인이 처치의 한 요인으로 고려될 때, 실험자료의 분석을 위한 혼합모형과 모형내 미지모수의 추론을 위한 방법을 논의한다. 반복측정 요인으로 공간요인을 고려하고 공간요인의 수준은 분할구에 할당되나 연구자가 임의로 배정할 수 없는 실험환경이 가정된다. 이러한 실험의 특성을 갖는 자료벡터의 확률분포로 복합대칭의 공분산 구조를 갖는 다변량 정규분포를 논의하고 있다. 또한, 가정된 실험환경에 부합하는 적합한 자료의 예를 통하여 제시된 모형의 타당성과 관련모수들의 추론방법을 다루고 있다.