• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2007년도 춘계학술대회 논문집
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• pp.397-399
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• 2007

This paper presents multiple regression analysis and data update to improve present spatial electric load forecasting algorithm of the DISPLAN. Spatial electric load forecasting considers a local economy, the number of local population and load characteristics. A Case study is performed for Jeon-Ju and analyzes a trend of the spatial load for the future 20 years. The forecasted information can contribute to an asset management of distribution systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.183-183
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• 2000

In this paper, web-based remote monitoring for cold-rolling system is developed and the analysis of spatial control system is performed. The remote monitoring system is able to grasp the status of cold-rolling system regardless of time and locations. We analyzed spatial control algorithm of the system with the collected data. The usefulness of spatial control system is shown by simulation studies.

• 한국지능시스템학회논문지
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• 제22권4호
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• pp.515-520
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• 2012

In brain computer interface (BCI) system, the most important part is classification of human thoughts in order to translate into commands. The more accuracy result in classification the system gets, the more effective BCI system is. To increase the quality of BCI system, we proposed to reduce noise and artifact from the recording data to analyzing data. We used auditory stimuli instead of visual ones to eliminate the eye movement, unwanted visual activation, gaze control. We applied independent component analysis (ICA) algorithm to purify the sources which constructed the raw signals. One of the most famous spatial filter in BCI context is common spatial patterns (CSP), which maximize one class while minimize the other by using covariance matrix. ICA and CSP also do the filter job, as a raw filter and refinement, which increase the classification result of linear discriminant analysis (LDA).

• 한국측량학회지
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• 제32권3호
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• pp.225-231
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• 2014

When a spatial regression model that uses kernel density values as a dependent variable is applied to retail business data, a unique model cannot be selected because kernel density values change following kernel bandwidths. To overcome this problem, this paper suggests how to use the point pattern analysis, especially the L-index to select a unique spatial regression model. In this study, kernel density values of retail business are computed by the bandwidth, the distance of the maximum L-index and used as the dependent variable of spatial regression model. To test this procedure, we apply it to meeting room business data in Seoul, Korea. As a result, a spatial error model (SEM) is selected between two popular spatial regression models, a spatial lag model and a spatial error model. Also, a unique SEM based on the real distribution of retail business is selected. We confirm that there is a trade-off between the goodness of fit of the SEM and the real distribution of meeting room business over the bandwidth of maximum L-index.

• 응용통계연구
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• 제21권3호
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• pp.387-397
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• 2008

최근 공간통계를 이용한 많은 연구가 진행되고 있고 공간통계학을 접목한 소지역 추정(small area estimation) 방법이 좋은 결과를 주고 있는 것으로 알려져 있다 소지역 추정에 사용되는 격자자료(lattice data) 분석에서 이웃정보를 정의하는 것은 자료 분석의 성패를 결정짓는 매우 중요한 부분이다. 그러나 기존에 사용된 대부분의 이웃정보시스템은 경계선을 공유할 때 이웃으로 정하는 방법을 사용하고 있다. 이에 본 논문에서는 경계선 공유를 이용한 이웃정보시스템 뿐 아니라 다른 여러 이웃정보시스템을 구하는 방법을 설명하고 2001년 경제활동자료를 이용하여 이 시스템들을 비교하였다

• Journal of Information Technology Applications and Management
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• 제13권1호
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• pp.137-147
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• 2006

Spatiotemporal data are records of the spatial changes of moving objects over time. Most data in corporate databases have a spatiotemporal nature, but they are typically treated as merely descriptive semantic data without considering their potential visual (or cartographic) representation. Businesses such as geographical CRM, location-based services, and technologies like GPS and RFID depend on the storage and analysis of spatiotemporal data. Effectively handling the data analysis process may be accomplished through spatiotemporal data warehouse and spatial OLAP. This paper proposes a multidimensional model for spatiotemporal data analysis, and cartographically represents the results of the analysis.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2006년도 춘계 학술발표회 논문집
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• pp.1046-1053
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• 2006

In the large scale recent reclaiming works performed within the wide spatial boundary, evaluation of long-term consolidation settlement and residual settlement of the whole construction area is sometimes made with the results of the limited ground investigation and measurement. Then the reliability of evaluation has limitations due to the spatial uncertainty. Additionally, in case of large scale deep excavation works such as urban subway construction, there are a lot of hazardous elements to threaten the safety of underground pipes or adjacent structures. Therefore it is necessary to introduce a damage prediction system of adjacent structures and others. For the more accurate analysis of monitoring information in the wide spatial boundary works and large scale urban deep excavations, it is necessary to perform statistical and spatial analysis considering the geographical spatial effect of ground and monitoring information in stead of using diagrammatization method based on a time-series data expression that is traditionally used. And also it is necessary that enormous ground information and measurement data, digital maps are accumulated in a database, and they are controlled in a integrating system. On the abovementioned point of view, we developed Geomonitor 2.0, an Internet based real time monitoring program with a new concept by adding GIS and geo-statistical analysis method to the existing real time integrated measurement system that is already developed and under useful use. The new program enables the spatial analysis and database of monitoring data and ground information, and helps the construction- related persons make a quick and accurate decision for the economical and safe construction.

• Communications for Statistical Applications and Methods
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• 제12권1호
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• pp.241-252
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• 2005

In this study we suggest that the spatial correlation structure of the brain fMRI data be used to characterize the functional connectivity of the brain. For some concussion and recovery data, we examine how the correlation structure changes from one step to another in the data analyses, which will allow us to see the effect of each analysis to the spatial correlation or the functional connectivity of the brain. This will lead us to spot the processes which cause significant changes in the spatial correlation structure of the brain. We discuss whether or not we can decompose correlation matrices in terms of its causes of variations in the data.

• 한국IT서비스학회지
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• 제15권3호
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• pp.211-221
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• 2016

The human spatial mobility information is in high demand in various businesses; however, there are only few studies on human mobility because spatio-temporal data is insufficient and difficult to collect. Now with the spread of smartphones and the advent of social networking services, the spatio-temporal data began to occur on a large scale, and the data is available to the public. In this work, we compared the movement behavior of residents and tourists by using geo-tagged tweets which contain location information. We chose Seoul to be the target area for analysis. Various creative concepts and analytical methods are used: grid map concept, cells visited concept, reverse geocoding concept, average activity index, spatial mobility index, and determination of residents and visitors based on the number of days in residence. Conducting a series of analysis, we found significant differences of the movement behavior between local residents and tourists. We also discovered differences in visiting activity according to residential countries and used applications. We expect that findings of this research can provide useful information on tourist development and urban development.

• Spatial Information Research
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• 제10권2호
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• pp.233-246
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• 2002

본 연구에서는 GIS의 공간통계분석을 활용하여 지가 연구에 일반적으로 활용되고있는 특성가격모형에서 입지적 특성이 갖는 영향력을 계량적으로 설명하기 위한 분석방법을 제시하였다. 여기에는 GIS 공간분석방법 가운데 중첩과 내삽 기능을 이용한 공간자료의 처리 과정이 포함되었다. 사례연구를 위해 동대문구 회기동의 1421개 개별지가에서 54개 표준지들을 추출하여 표준지의 중심좌표를 구하고, 이 벡터 자료점들과 공간적 관련성에 기초하여 조사되지 않은 지점의 지가 예측값을 확률적으로 평가할 수 있는 크리깅 분석방법을 적용하였다. 특히 이러한 분석 과정에서 변동도를 통해 분석한 공간적 자기상관관계는 공간 의존성의 형성과정을 추정할 때 장점이 있음을 밝혔다.