• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 2008년도 연합학회학술대회
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• pp.477-486
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• 2008

This paper examines the evolution issues of regional tourism resources in complicated and networked industry the perspective of co-evolution types and dualism. Regional tourism structure has been changing more and faster according to various attractions and internal and external environment; natural resources, facilities, festivals and events, drama and movies, and public resources, etc. This paper approaches Olikowski's dualism perspective as a theoretical view about the alliance network between region's attractions and tourism industry in Korea. Exploratory analysis was explained the dualism cases performed on the matrix between resource characteristics and alliance complexity on human resources based on regional tourism industry.

• ETRI Journal
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• 제44권2호
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• pp.208-219
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• 2022

Crime amount prediction is crucial for optimizing the police patrols' arrangement in each region of a city. First, we analyzed spatiotemporal correlations of the crime data and the relationships between crime and related auxiliary data, including points-of-interest (POI), public service complaints, and demographics. Then, we proposed a crime amount prediction model based on 2D convolution and long short-term memory neural network (2DCONV-LSTM). The proposed model captures the spatiotemporal correlations in the crime data, and the crime-related auxiliary data are used to enhance the regional spatial features. Extensive experiments on real-world datasets are conducted. Results demonstrated that capturing both temporal and spatial correlations in crime data and using auxiliary data to extract regional spatial features improve the prediction performance. In the best case scenario, the proposed model reduces the prediction error by at least 17.8% and 8.2% compared with support vector regression (SVR) and LSTM, respectively. Moreover, excessive auxiliary data reduce model performance because of the presence of redundant information.

• International Journal of Computer Science & Network Security
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• 제21권11호
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• pp.43-48
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• 2021

The article proposes a method of modeling a comprehensive indicator for evaluating the effectiveness of regional management of innovation activity. This will make it possible to assess the effectiveness of personnel, financial and credit and foreign economic activity of the regions from the standpoint of an integrated approach. The modeling technique is proposed to be carried out using the tools of taxonomic analysis and the calculation of a complex indicator of the effectiveness of the innovation activity management.

• 대한지리학회지
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• 제46권3호
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• pp.351-365
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• 2011

본 연구는 지역자원기반산업의 지역경제공간의 형성을 살펴보는 것을 목적으로 한다. 본 연구에서는 기존의 기업 네트워크 분석방법과 가치사슬의 개념을 통합하는 연구틀을 고안하였다. 주활동으로 원료구매에서 생산, 판매에 이르는 기업활동 네트워크를 살펴보았으며, 지원활동으로 연구개발과 기업지원서비스 네트워크를 살펴보았다. 이 연구틀을 기반으로 지역자원기반산업을 유형화하고 이 유형들을 종합하여 살펴봄으로써, 지역자원기반산업의 공간적 특성을 살펴볼 수 있었다. 본 연구에서는 이 연구틀을 소개하고 한국 대표적인 지역자원기반산업인 장류제조업에 적용하여, 장류산업의 기업활동 네트워크를 분석하고, 이를 종합하여 지역자원기반산업의 역동성을 살펴보았다.

• 지역연구
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• 제15권2호
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• pp.75-102
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• 1999

This paper attempts at analyzing the urban dynamics in Northeast Asia by looking at major forces transforming the regional structure of Northeast Asia. Trade and foreign direct invest-ment are identified as two principal channels of increasing economic interdependence in the region. In addition, macro development strategy and infrastructure policy are another set of determining factors for changes in the regional structure of Northeast Asia. To examine the role of cities and inter-city linkages, the paper first tries to identify major urban centers and urban hierarchy in Northeast Asia. Secondly, it examines the prospects for inter-city network formation. Against these anticipated changes in the regional structure and inter-city networks in Northeast Asia, the paper discusses about the future of Korea as well as the role of Koran cities in the regional economy of Northeast Asia.

• 대한지리학회지
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• 제36권4호
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• pp.402-417
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• 2001

본 연구에서는 사업서비스 분야 한국내 외국인직접투자가 지역경제에 미치는 영향을 분석하였으며, 특히, 지역네트워크와 지식의 활용이라는 측면에서 파악하였다. 외국인직접투자기업은 한국내 시장확보라는 투자동기에 따라 고객과의 네트워크, 공급 네트워크는 높은 비중을 나타내고 있으나, 상대적으로 산학연계 및 협회, 조합, 정부기관과의 관계는 낮게 나타난다. 한국내 지식이전 및 상호작용도 투자모기업의 정책에 따라 제한적으로 이루어지고 있다. 그러나, 협력관계 및 인력이동 등 장기적으로 볼 때 긍정적인 측면과 가능성도 보이고 있어, 지식활용에 기반한 정책지원 및 활용안을 수립하여 실천한다면, 외국인기업이 충분히 지역내 뿌리내리며, 지역경제에 기여할 수 있을 것이다.

• 대기
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• 제16권4호
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• pp.259-267
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• 2006

In the present study, the neural network (NN) model with cluster analysis method was developed to predict storm surge in the whole Korean coastal regions with special focuses on the regional extension. The model used in this study is NN model for each cluster (CL-NN) with the cluster analysis. In order to find the optimal clustering of the stations, agglomerative method among hierarchical clustering methods was used. Various stations were clustered each other according to the centroid-linkage criterion and the cluster analysis should stop when the distances between merged groups exceed any criterion. Finally the CL-NN can be constructed for predicting storm surge in the cluster regions. To validate model results, predicted sea level value from CL-NN model was compared with that of conventional harmonic analysis (HA) and of the NN model in each region. The forecast values from NN and CL-NN models show more accuracy with observed data than that of HA. Especially the statistics analysis such as RMSE and correlation coefficient shows little differences between CL-NN and NN model results. These results show that cluster analysis and CL-NN model can be applied in the regional storm surge prediction and developed forecast system.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 1998년도 학술발표회 논문집
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• pp.7-13
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• 1998

본 연구에서는 공간적으로 분포되어 있는 연강우량 자료를 이용한 지역 기상학 적인 가뭄을 정의하고 해석하는 모형을 제시한다. 비선형, 비매변수법에 기초한 공간 해석 신경망 (Spatial Analysis Neural Network:SANN)모형을 이용하여, 각 년에 대하여 공간의 임의 점에 서 의 극심, 심, 경심, 및 비 가뭄 확률을 전 대상 지역에 대하여 산출을 통하여 가뭄확률도를 작성 하며, Bayesian 가뭄 심도 지수 (BDSI)를 통하여 전 대상 지역을 가장 적절하게 극심, 심, 경심, 미 가뭄 지역으로 분류하는 방법을 제시한다. 또한, 각 년의 대표적인 가뭄의 형태를 제시 하여 줄 수 있는 지역 가뭄확률과 지역 가뭄 확률 지수를 소개한다. 이 모든 시공간의 가뭄 해석의 방법 은 실제로 우리나라(남한) 전역에 대하여 실시하여, 과거 1967년부터 1996년 까지 의 공간적이고 시간적인 가뭄의 발생 현황과 그 특징을 조사한다. 이는 우리나라 장기 수자원 개발 및 유역 관 리를 더욱 정량적인 가뭄정보에 의해 수행하게하여 줄 수 있을 것이다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.170-170
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• 2020

Due to the development of technologies, complex computation of huge data set is possible with a prevalent personal computer. Therefore, machine learning methods have been widely applied in the hydrologic field such as regression-based regional frequency analysis (RFA). The main purpose of this study is to compare two frameworks of RFA based on the artificial neural network (ANN) models: quantile regression technique (QRT-ANN) and parameter regression technique (PRT-ANN). As an output layer of the ANN model, the QRT-ANN predicts quantiles for various return periods whereas the PRT-ANN provides prediction of three parameters for the generalized extreme value distribution. Rainfall gauging sites where record length is more than 20 years were selected and their annual maximum rainfalls and various hydro-meteorological variables were used as an input layer of the ANN model. While employing the ANN model, 70% and 30% of gauging sites were used as training set and testing set, respectively. For each technique, ANN model structure such as number of hidden layers and nodes was determined by a leave-one-out validation with calculating root mean square error (RMSE). To assess the performances of two frameworks, RMSEs of quantile predicted by the QRT-ANN are compared to those of the PRT-ANN.

• 국토계획
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• 제53권7호
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• pp.5-22
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• 2018

While the competitiveness of small and medium sized cities has become important for balanced development at the national scale, they have experienced continuous decline in population and employment, particularly those in non-capital regions. In addition, some of small and medium sized cities have been classified into shrinking cities that have declined due to their long-term structural reasons. To address these issues, a regional approach, by which a hub city and its surrounding small and medium sized cities can collaborate has been suggested. Given this background, the purpose of this study is to identify and delineate hub cities and their impact areas by using travel data as a functional network index. This study uses a centrality index to identify the hub cities of small and medium sized cities and Markov-chain model and cluster analysis to delineate regional boundaries. The mean first passage time (MFPT) generated from the Markov-chain model can be interpreted as functional distance of each region. The study suggests a methodological approach delineating the boundaries of regions incorporating functional relationships of hub cities and their impact areas, and provides 59 hub cities and their impact areas. The results also provide policy implications for regional spatial planning that addresses appropriate planning boundaries of regions for enhancing the economic competitiveness of small and medium sized cities and ensuring services for shrinking cities.