• Title/Summary/Keyword: 센서스데이터

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Forecasting Electric Power Demand Using Census Information and Electric Power Load (센서스 정보 및 전력 부하를 활용한 전력 수요 예측)

  • Lee, Heon Gyu;Shin, Yong Ho
    • Journal of Korea Society of Industrial Information Systems
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    • v.18 no.3
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    • pp.35-46
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    • 2013
  • In order to develop an accurate analytical model for domestic electricity demand forecasting, we propose a prediction method of the electric power demand pattern by combining SMO classification techniques and a dimension reduction conceptualized subspace clustering techniques suitable for high-dimensional data cluster analysis. In terms of electricity demand pattern prediction, hourly electricity load patterns and the demographic and geographic characteristics can be analyzed by integrating the wireless load monitoring data as well as sub-regional unit of census information. There are composed of a total of 18 characteristics clusters in the prediction result for the sub-regional demand pattern by using census information and power load of Seoul metropolitan area. The power demand pattern prediction accuracy was approximately 85%.

Raft-D: A Consensus Algorithm for Dynamic Configuration of Participant Peers (Raft-D: 참여 노드의 동적 구성을 허용하는 컨센서스 알고리즘)

  • Ha, Yeoun-Ui;Jin, Jae-Hwan;Lee, Myung-Joon
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.2
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    • pp.267-277
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    • 2017
  • One of fundamental problems in developing robust distributed services is how to achieve distributed consensus agreeing some data values that should be shared among participants in a distributed service. As one of algorithms for distributed consensus, Raft is known as a simple and understandable algorithm by decomposing the distributed consensus problem into three subproblems(leader election, log replication and safety). But, the algorithm dose not mention any types of dynamic configuration of participant peers such as adding new peers to a consensus group or deleting peers from the group. In this paper, we present a new consensus algorithm named Raft-D, which supports the dynamic configuration of participant peers by extending the Raft algorithm. For this, Raft-D manages the additional information maintained by participant nodes, and provides a technique to check the connection status of the nodes belonging to the consensus group. Based on the technique, Raft-D defines conditions and states to deal with adding new peers to the consensus group or deleting peers from the group. Based on those conditions and states, Raft-D performs the dynamic configuration process for a consensus group through the log update mechanism of the Raft algorithm.

A Study on Improvements of Multi-Dimensional Flood Damage Analysis using Census Data (센서스 자료를 활용한 다차원홍수피해산정법 개선 연구)

  • Kim, Gil ho;Kim, Duck hwan;Choi, Cheon kyu;Kim, Kyung tak
    • Proceedings of the Korea Water Resources Association Conference
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    • 2016.05a
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    • pp.576-576
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    • 2016
  • 치수경제성분석, 투자우선순위 및 시설물 규모결정 등의 의사결정과정에서 실무에서는 다차원 홍수피해산정법(MD-FDA)을 현재까지 널리 사용 중이다. 2004년에 개발된 MD-FDA는 대상지역의 자산규모를 행정구역 경계 최소단위인 "읍면동"을 기준으로 계산하여 취합하고, 대상자산이 위치가능한 토지이용정보를 토지피복도로부터 확인하여, 읍면동내 토지이용공간면적을 기준으로 자산정보를 분배(분해)하는 방식으로 이루어진다. 그러나 읍면동 단위의 공간적인 범위는 상당한 면적의 공간적 경계이기 때문에, 이를 평균적인 밀도데이터로 분배 시 공간적인 자산분포에 대해 정밀도를 담보할 수 없다. 이에 본 연구는 행정구역경계인 "읍면동"과 비교할 때 평균적으로 1/30의 면적을 가지는 집계구 단위의 센서스 공간정보자료를 이용하여 방법론을 개선하였고, 이를 MD-FDA 분석체계를 근간으로 센서스자료와 관계된 자료들 간의 연계 및 전체적인 분석과정을 정립하였다. 본 연구에서 제안한 방법을 경기도 동두천시를 대상으로 적용하여 기존 방법에 의한 피해액과 그 차이를 비교하였고, 도로명전자지도의 실제 건물객체 자료(.shp)를 기준으로 오차율을 확인한 결과, 기존 방식에 비해 정밀도가 월등히 향상된 것을 확인할 수 있었다.

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A Study on Estimates to Longevity Population of Small Area and Distribution Patterns using Vector based Dasymetric Mapping Method (벡터기반 대시매트릭 기법을 이용한 소지역 장수인구 추정 및 분포패턴에 관한 연구)

  • Choi, Don-Jeong;Kim, Young-Seup;Suh, Yong-Cheol
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.29 no.5
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    • pp.479-485
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    • 2011
  • A number of case studies that find distribution of longevity population and influencing factors through the spatial data fusion using GIS techniques are growing. The majority cases of these studies are adopt census administrative boundary data for the spatial analysis. However, these methods cannot fully explain the phenomenon of longevity because there are a variety of spatial characteristics within the census administrative boundaries. Therefore, studies of spatial unit are required that realistically reflect the phenomenon of human longevity. The dasymetric mapping method enables to product of spatial unit more realistic than census administrative boundary map and statistic estimates of small area utilizing diversity spatial information. In this study, elderly population of small area has been estimated within statistically significant level that applied the vector based dasymetric mapping method. Also, the cluster analysis confirmed that the variation of local spatial relationship within census administrative boundary. The result of this study implied that the need for local-level studies of the human longevity and the validity of the dashmetric mapping techniques.

한국 센서스데이터의 MAUP

  • 강계화
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2003.11a
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    • pp.3-8
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    • 2003
  • Census data are usually provided at an aggregated level. However, the aggregated data are essentially arbitrary geographical areas. The areal units used to report census data have no natural or meaningful geographical identity. Unfortunately, this means that analyses of these area aggregations may be conditional upon the set of zones, which are presented. This effect is known as the modifiable areal unit problem (MAUP) and has two related aspects. First, scale effect is the variation in numerical results that occurs due to the number of zones used in an analysis. Second, results may also differ between different ways of aggregating exactly the same data to the same scale; this may be called the aggregation effect (Openshaw, 1984). This study aims to provide a practical tool for the study of MAUP. I have created a set of 91 areal units based on 280 basic units in Nonhyun-2 dong to solve zoning problem and scale problem. We can easily recognize the importance of areal classification as statistics were different according to areal classification.

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An examination of Akers' Social Strcture and Social Learning Model with PHDCN Data (미국의 PHDCN 데이터를 사용한 Akers의 사회구조 및 사회학습이론에 대한 다층적 회귀분석연구)

  • Kim, Eunyoung;Park Junseok
    • Journal of the Society of Disaster Information
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    • v.8 no.4
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    • pp.384-390
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    • 2012
  • This study attempts to test the effects of neighborhoods on children and adolescents' alcohol, cigarette and marijuana use. Theoretically, this study was guided by Akers' (1998) SSSL model as potential explanations for understanding the linkage and provided partial test of the model. More specifically, it aims to test the mediation effects of one of core propositions of the SSSL model; whether differential association with deviant peers as well as with conforming peers mediates social disorganization of neighborhoods on adolescent substance and drug use in a different direction. Using multilevel regression techniques with robust standard error, this study utilized data from 1,791 children and adolescents who were nested in 80 neighborhoods in Chicago. The findings of the study provide mixed supports for the SSSL model. That is, it found that there are not only mediation effects but also moderation effects of differential association on children and adolescents' substance and drug use.

Data Server Mining applied Neural Networks in Distributed Environment (분산 환경에서 신경망을 응용한 데이터 서버 마이닝)

  • 박민기;김귀태;이재완
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.05a
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    • pp.473-476
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    • 2003
  • Nowaday, Internet is doing the role of a large distributed information service tenter and various information and database servers managing it are in distributed network environment. However, the we have several difficulties in deciding the server to disposal input data depending on data properties. In this paper, we designed server mining mechanism and Intellectual data mining system architecture for the best efficiently dealing with input data pattern by using neural network among the various data in distributed environment. As a result, the new input data pattern could be operated after deciding the destination server according to dynamic binding method implemented by neural network. This mechanism can be applied Datawarehous, telecommunication and load pattern analysis, population census analysis and medical data analysis.

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A Method for Generating Large-Interval Itemset using Locality of Data (데이터의 지역성을 이용한 빈발구간 항목집합 생성방법)

  • 박원환;박두순
    • Journal of Korea Multimedia Society
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    • v.4 no.5
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    • pp.465-475
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    • 2001
  • Recent1y, there is growing attention on the researches of inducing association rules from large volume of database. One of them is the method that can be applied to quantitative attribute data. This paper presents a new method for generating large-interval itemsets, which uses locality for partitioning the range of data. This method can minimize the loss of data-inherent characteristics by generating denser large-interval items than other methods. Performance evaluation results show that our new approach is more efficient than previously proposed techniques.

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An Efficient Algorithm Using the locality of Data for Mining Quantitative Association Rules (수량 연관규칙 생성을 위한 데이터의 지역성을 고려한 효과적인 알고리즘 제안)

  • 이혜정;박원환;박두순
    • Proceedings of the Korea Multimedia Society Conference
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    • 2003.05b
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    • pp.126-129
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    • 2003
  • 최근 대용량의 데이터베이스로부터 연관규칙을 발견하여 이를 활용하는 단계에서 이러한 연관규칙을 수량항목에도 적용할 수 있도록 확장하는 연구가 소개되고 있다. 본 논문에서는 수량 항목을 이진항목으로 변환하기 위하여 빈발구간 항목집합(Large Interval Itemsets)을 생성할 때 수량 항목이 특정 영역에 집중하여 발생하거나 골고루 분포되어 있지 않은 경우, 이러한 지역성(locality)을 고려하여 빈발구간 항목집합을 생성하는 방법을 제안한다. 이 방법은 기존의 방법보다 많은 수의 세밀한 빈발구간 항목들을 생성할 수 있을 뿐만 아니라 의미 있는 구간을 중심으로 빈발구간 항목들이 순서대로 생성되기 때문에 세밀도를 판단하여 활용할 수 있으며, 원 데이터가 가지고 있는 특성의 손실을 최소화할 수 있는 특징이 있다 또한 인구센서스등 실 데이터를 사용한 성능평가를 통하여 기존의 방법보다 우수함을 보였다.

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A Comparative Analysis of Areal Interpolation Methods for Representing Spatial Distribution of Population Subgroups (하위인구집단의 분포 재현을 위한 에어리얼 인터폴레이션의 비교 분석)

  • Cho, Daeheon
    • Spatial Information Research
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    • v.22 no.3
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    • pp.35-46
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    • 2014
  • Population data are usually provided at administrative spatial units in Korea, so areal interpolation is needed for fine-grained analysis. This study aims to compare various methods of areal interpolation for population subgroups rather than the total population. We estimated the number of elderly people and single-person households for small areal units from Dong data by the different interpolation methods using 2010 census data of Seoul, and compared the estimates to actual values. As a result, the performance of areal interpolation methods varied between the total population and subgroup populations as well as between different population subgroups. It turned out that the method using GWR (geographically weighted regression) and building type data outperformed other methods for the total population and households. However, the OLS regression method using building type data performed better for the elderly population, and the OLS regression method based on land use data was the most effective for single-person households. Based on these results, spatial distribution of the single elderly was represented at small areal units, and we believe that this approach can contribute to effective implementation of urban policies.