• The Journal of Engineering Geology
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• v.23 no.2
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• pp.137-147
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• 2013

For the effective management of groundwater resources, it is necessary to predict groundwater level fluctuations in response to rainfall events. In the present study, time series models using artificial neural networks (ANNs) and support vector machines (SVMs) have been developed and applied to groundwater level data from the Gasan, Shingwang, and Cheongseong stations of the National Groundwater Monitoring Network. We designed four types of model according to input structure and compared their performances. The results show that the rainfall input model is not effective, especially for the prediction of groundwater recession behavior; however, the rainfall-groundwater input model is effective for the entire prediction stage, yielding a high model accuracy. Recursive prediction models were also effective, yielding correlation coefficients of 0.75-0.95 with observed values. The prediction errors were highest for Shingwang station, where the cross-correlation coefficient is lowest among the stations. Overall, the model performance of SVM models was slightly higher than that of ANN models for all cases. Assessment of the model parameter uncertainty of the recursive prediction models, using the ratio of errors in the validation stage to that in the calibration stage, showed that the range of the ratio is much narrower for the SVM models than for the ANN models, which implies that the SVM models are more stable and effective for the present case studies.

• Economic and Environmental Geology
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• v.45 no.5
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• pp.579-587
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• 2012

The purpose of this study is to emphasize the necessity of extention of a government R&D planning scope. Presently, government R&D planning is focused on the selecting a R&D project. There is no R&D strategy for R&D conducting such as the composition of R&D team, collaboration and knowledge flow. Ordinarily these strategies are established by research director. This study analyzed the determinants of excellent R&D performance and proposed R&D strategy for R&D conducting using the patent bibliograpy information in energy resources production technology field. On the other hand, this study introduced the concept of technology lifecycle and showed that R&D strategy should be differentiated by technology lifecycle.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.129-134
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• 2017

This study aims to develop the traffic accident models by circular intersection type using count data model. The number of accident, the number of fatal and injured persons(FSI), and EPDO are calculated from the traffic accident data of TAAS. The circular intersection accident models are developed through Poisson and negative binomial regression analysis. The main results of this study are as follows. First, the null hypotheses that there are differences in the number of traffic accidents, FSI and EPDO by type of circular intersections are rejected. Second, the scale of intersection(median, large), number of approach road, mean width and length of exit road, area of the circulating roadway and central island are selected as factors influencing the number of traffic accidents, FSI and EPDO in rotary. Third, the scale of intersection(median), guide signs(limited speed, direction, roundabout), number of approach road, entry angle, area of the intersection and central island are adopted as factors influencing the number of traffic accidents, FSI and EPDO in roundabout. Finally, transferring from rotary to roundabout could be expected to make the accident decrease.

• The Korean Journal of Community Living Science
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• v.22 no.2
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• pp.247-255
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• 2011

This study analyzed the demand for a community-based tourism site using a poisson model, a negative binominal model, a truncated poisson model and a truncated negative binominal model as count data models. For these reasons, questionnaire surveys were conducted into 5 community-based tourism sites in Chuncheon city with 406 tourists, and was analyzed using the STATA program. The fitness levels of four models were significant(p=0.0000) using a likelihood ratio test. The study results suggest that the demand of community-based tourism sites for visiting tourists was influenced by a pre-visiting experience, recognition of sustainable tourism, visitation of downtown, purchase of souvenir or farm produce, conversation with regional residents, regional harmony, preservation of natural resources and sex within the poisson and truncated poisson models. However, the variables of visitation of downtown, preservation of natural resources and sex were not significant within the negative binominal model and the visitation of downtown and preservation of natural resources were not significant within the truncated negative binominal model. The results of the visiting demand of community-based tourism sites can provide information for sustainable regional development strategies.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.144-145
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• 2023

육상, 철도, 항공 등 타 교통분야에서 지속적으로 사고와 인명피해가 줄어든 반면, 해양분야는 해양사고가 증가하며 실효적 해양교통안전관리에 대한 필요성이 대두되고 있다. 최근 3년간 국내 해상에서 발생한 충돌사고 중 어선을 포함한 충돌사고가 전체의 약 84%를 차지하며, 해상교통의 주요 변수인 어선을 포함한 국가의 해상교통량 파악은 반드시 필요한 실정이다. 본 연구에서는 현 정부 국정과제인 '디지털 해상 교통망 구축'과 더불어 해양교통안전관리체계 마련의 일환으로 국내 전체 선박위치발신장치(AIS, V-PASS) 데이터를 활용하여 해상교통량을 분석하고 예측 모델을 개발한다. 이를 위해 선박 밀집도를 통한 그리드별 공간가산분석과 항적 데이터 전처리 및 선형화, 선박 길이에 따른 점용면적 산정을 통한 단위 그리드별 해상교통량을 분석한다. 또한, 과거 교통량 데이터는 딥러닝 기반의 시계열 특성을 지닌 RNN과 LSTM 모델을 활용하여 교통량 예측 모형을 개발한다. 본 연구의 결과는 해상교통량과 해양사고의 연관성 분석 및 속력제한구역 등 해상정책 수립의 정량적 근거를 제공하며, 국민에게 해상교통정보 제공을 통해 교통복지 증진에 기여할 수 있다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.146-147
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• 2023

해양사고는 도로교통과 달리 지속적으로 증가하고 있으며, 인명피해가 주로 발생하는 주요 사고의 치사율은 도로교통의 11.7배 이상이다. 해양사고는 외부 환경에 따라 사고 위치가 변하고 즉각적인 조치가 어려워 타 교통에 비해 대형 사고로 이어질 가능성이 매우 크다. 그러나 여전히 사고가 발생하고 난 후 대응하는 등 사후적 관리 단계에 무르고 있어 사고의 주요 요인을 사전에 식별·관리하는 선제적 관리단계로의 전환 필요성이 대두되고 있다. 따라서 본 연구에서는 해양사고 발생 지점 밀도 기반의 가변 공간 군집체계를 반영한 해양사고 예측모델을 개발하였다. 반복적인 공간 가산분석을 통해 밀도가 높을수록 작은 규모의 격자 체계를 가질 수 있도록 상세한 공간 군집체계를 구성하였으며, 단순 사고 위험도 예측뿐만 아닌 사고 인과관계를 설명할 수 있는 BN(Bayesian Network) 기반의 모형을 사용하여 해양사고 위험예측 모델을 개발하였다. 또한, Cost-of-Omission을 통해 해양사고 예측확률의 변화와 각 변수들의 영향력을 확인하였으며, 월별 해양사고예측 결과를 GIS를 활용하여 2D/3D 기반으로 시각화하였다.

• Journal of the Economic Geographical Society of Korea
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• v.19 no.1
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• pp.1-17
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• 2016

This paper attempts to explore the spatial structure of inventor networks and their determinants among 230 shi-gun-gu regions in Korea by investigating the residence of co-inventors engaged in Korean patent applications to the Korean Intellectual Office and exploiting a zero inflated negative binomial model to accommodate an estimation to the count nature of a dependent variable and its excess of zeros. Several variables are found to affect the spatial linkage of inventor networks. Spatial links extend beyond the region if it has more own R&D-related specific assets (private R&D, patent productivity, population, education); if it is physically close to and has technological similarity with the other region. The assets of the other region plays a positive role if, in a similar way, the other region has more R&D-related specific assets.

• The Journal of Fisheries Business Administration
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• v.38 no.2
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• pp.79-101
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• 2007

The purpose of this study is to estimate the economic value of the Songieong Beach in Off-season, using a Individual Travel Cost Model(ITCM). Songieong Beach is located in Busan but far away from city. These days, however, the increased rate of traffic inflow to the Songieong beach and the five-day working week are reflected in the trend analysis. Moreover, people have changed psychological value. For that reason, visitors are on the increase on the beach in off-season. The ITCM is applied to estimate non-market value or environmental Good like a Contingent Valuation Method and Hedonic Price Model etc. The ITCM was derived from the Count Data Model(i.e. Poisson and Negative Binomial model). So this paper compares Poisson and negative binomial count data models to measure the tourism demands. The data for the study were collected from the Songjeong Beach on visitors over the a week from November 1 through November 23, 2006. Interviewers were instructed to interview only individuals. So the sample was taken in 113. A dependent variable that is defined on the non-negative integers and subject to sampling truncation is the result of a truncated count data process. This paper analyzes the effects of determinants on visitors' demand for exhibition using a class of maximum-likelihood regression estimators for count data from truncated samples, The count data and truncated models are used primarily to explain non-negative integer and truncation properties of tourist trips as suggested by the economic valuation literature. The results suggest that the truncated negative binomial model is improved overdispersion problem and more preferred than the other models in the study. This paper is not the same as the others. One thing is that Estimating Value of the Beach in off-season. The other thing is this study emphasizes in particular 'travel cost' that is not only monetary cost but also including opportunity cost of 'travel time'. According to the truncated negative binomial model, estimates the Consumer Surplus(CS) values per trip of about 199,754 Korean won and the total economic value was estimated to be 1,288,680 Korean won.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.817-827
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• 2014

In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. The degradation results in noise and blurring which badly affect identification and extraction of useful information in image data. This study proposes a maximum a posteriori (MAP) estimation using Point-Jacobian iteration to restore a degraded image. The proposed method assumes a Gaussian additive noise and Markov random field of spatial continuity. The proposed method employs a neighbor window of spoke type which is composed of 8 line windows at the 8 directions, and a boundary adjacency measure of Mahalanobis square distance between center and neighbor pixels. For the evaluation of the proposed method, a pixel-wise classification was used for simulation data using various patterns similar to the structure exhibited in high resolution imagery and an unsupervised segmentation for the remotely-sensed image data of 1 mspatial resolution observed over the north area of Anyang in Korean peninsula. The experimental results imply that it can improve analytical accuracy in the application of remote sensing high resolution imagery.

• Journal of Digital Convergence
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• v.9 no.6
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• pp.173-186
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• 2011

In this study, the influence of the CEOs' characteristics on the technology innovation performances of IT venture companies was analyzed. The relation between business performance and the characteristics of CEOs has been dealt with in earlier studies, but most paid attention to financial perspective, and few of these focused on the influence of managers on technology innovation. On the other hand, most of the studies related to the role of managers in technology innovation mainly focused on R&D investment and research infrastructure but did not delve on the characteristics of them in an in-depth way. In this study, the characteristics of CEOs and their technology innovation performances were empirically analyzed based on the results of a recently conducted survey on the IT venture companies. In the analytical aspect, a negative binominal model was applied to solve the over-dispersion problem that often appears in the count variable analysis. As a result, it was found that major, work type, and work experience, among managers' characteristics, have significant influences on managers' technology innovation performances, along with the company's innovation capacity, technological competitiveness, market competition, and support from the government.