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텍스트 마이닝을 활용한 지역 특성 기반 도시재생 유형 추천 시스템 제안
김익준(Ikjun Kim),이준호(Junho Lee),김효민(Hyomin Kim),강주영(Juyoung Kang) 한국지능정보시스템학회 2020 지능정보연구 Vol.26 No.3
현 정부의 주요 국책사업 중 하나인 도시재생 뉴딜사업은 매년 100 곳씩, 5년간 500곳을대상으로 50조를 투자하여 낙후된 지역을 개발하는 것으로 언론과 지자체의 높은 이목이 집중되고 있다. 그러나, 현재 이 사업모델은 면적 규모에 따라 “우리동네 살리기, 주거정비지원형, 일반근린형, 중심시가지형, 경제기반형” 등 다섯 가지로 나뉘어 추진되어 그 지역 본래의 특성을 반영하지 못하고 있다. 국내 도시재생 성공 키워드는 “주민 참여”, “지역특화” “부처협업”, “민관협력”이다. 성공 키워드에 따르면 지자체에서 정부에게 도시재생 사업을 제안할 때 지역주민, 민간기업의 도움과 함께 도시의 특성을 정확히 이해하고 도시의 특성에 어울리는 방향으로 사업을 추진하는 것이 가장 중요하다는 것을 알 수 있다. 또한 도시재생 사업 후 발생하는 부작용 중 하나인 젠트리피케이션 문제를 고려하면 그 지역 특성에 맞는 도시재생 유형을 선정하여 추진하는 것이 중요하다. 이에 본 연구는 ‘도시재생 뉴딜 사업’ 방법론의 한계점을 보완하기 위해, 기존 서울시가 지역 특성에 기반하여 추진하고 있는 “2025 서울시 도시재생 전략계획”의 도시재생 유형을 참고하여 도시재생 사업지에 맞는 도시재생 유형을 추천하는 시스템을 머신러닝 알고리즘을 활용하여 제안하고자 한다. 서울시 도시재생 유형은 “저이용저개발, 쇠퇴낙후, 노후주거, 역사문화자원 특화” 네 가지로 분류된다 (Shon and Park, 2017). 지역 특성을 파악하기 위해 총 4가지 도시재생 유형에 대해 사업이 진행된 22개의 지역에 대한 뉴스 미디어 10만여건의 텍스트 데이터를 수집하였다. 수집된 텍스트를 이용하여 도시재생 유형에 따른 지역별 주요 키워드를 도출하고 토픽모델링을 수행하여 유형별 차이가 있는 지 탐색해 보았다. 다음 단계로 주어진 텍스트를 기반으로 도시재생 유형을 추천하는 추천시스템 구축을 위해 텍스트 데이터를 벡터로 변환하여 머신러닝 분류모델을 개발하였고, 이를 검증한 결과 97% 정확도를 보였다. 따라서 본 연구에서 제안하는 추천 시스템은 도시재생 사업을 진행하는 과정에서 신규 사업지의 지역 특성에 기반한 도시재생 유형을 추천할 수 있을 것으로 기대된다. "The Urban Renewal New Deal project”, one of the government"s major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation”, when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the "Urban Regeneration New Deal Project" methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the "2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan" promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban rege
대용량 해석을 지원하는 무기체계 연구 개발 전용 모델러 설계 기술 연구
송일환(Ilhwan Song),김익준(Ikjune Kim),리경호(Jinggao Li),유용균(Yonggyun Yu),한순흥(Soonhung Han) (사)한국CDE학회 2010 한국CDE학회 논문집 Vol.15 No.1
Generation of over one hundred million mesh is essential for getting an exact analysis result of penetration, combustion, and explosion of missile. But because no domestic modeler to support this exists and a modeler only for missile also has not been developed yet, it is too difficult to get this goal. In this research we develop a modeler only for an engineering analysis of missile using 64bit computing system to solve current problems.
랩 어라운드 및 최대 볼륨 분해를 이용한 설계 특징형상 인식을 위한 볼륨 분해 방법
김병철(Byung Chul Kim),김익준(Ikjune Kim),한순흥(Soonhung Han),문두환(Duhwan Mun) 대한기계학회 2012 대한기계학회 춘추학술대회 Vol.2012 No.11
To modify product design easily, modern CAD systems adopt the feature-based model as their primary representation. On the other hand, the boundary representation (B-rep) model is used as their secondary representation. IGES and STEP AP203 ed.1 are the representative standard formats for the exchange of CAD files. Unfortunately, both of them only support the B-rep model. As a result, feature data are lost during the CAD file exchange based on these standards. Loss of feature data causes the difficulty of CAD model modification and prevents the transfer of design intent. To resolve this problem, a tool for recognizing design features from a B-rep model and then reconstructing a feature-based model with the recognized features should be developed. As the first part of this research, this paper presents a method for decomposing a B-rep model into volumes suitable for design feature recognition. The results of experiments with a prototype system are analyzed. From the analysis, future research issues are suggested.
김병철(Byung Chul Kim),김익준(Ikjune Kim),한순흥(Soonhung Han),문두환(Duhwan Mun) (사)한국CDE학회 2013 한국CDE학회 논문집 Vol.18 No.1
To modify product design easily, modern CAD systems adopt the feature-based model as their primary representation. On the other hand, the boundary representation (B-rep) model is used as their secondary representation. IGES and STEP AP203 edition 1 are the representative standard formats for the exchange of CAD files. Unfortunately, both of them only support the B-rep model. As a result, feature data are lost during the CAD file exchange based on these standards. Loss of feature data causes the difficulty of CAD model modification and prevents the transfer of design intent. To resolve this problem, a tool for recognizing design features from a B-rep model and then reconstructing a feature-based model with the recognized features should be developed. As the first part of this research, this paper presents a method for decomposing a B-rep model into simple volumes suitable for design feature recognition. The results of experiments with a prototype system are analyzed. From the analysis, future research issues are suggested.
KS 표준을 활용한 압력용기 설계 검증 시스템 프레임워크
이재철(Jaechul Lee),김익준(Ikjune Kim),임채호(Chae Ho Lim),황진상(Jinsang Hwang),문두환(Duhwan Mun) 대한기계학회 2015 大韓機械學會論文集A Vol.39 No.3
제품 규정에는 제조사가 준수해야 하는 제품에 관한 다양한 지침 및 규제사항이 담겨 있다. 이 연구에서는 KS 표준을 활용하여 압력용기의 설계 결과를 검증하는 시스템 프레임워크와 구성 요소들을 제안한다. 그리고 기간 시스템으로부터 설계 템플릿 데이터를 생성하는 방법과 규정 지식베이스를 구축하는 방법을 제시한다. 마지막으로 압력용기 설계 검증 시스템을 구현하고 테스트 데이터를 활용한 실험을 통해 시스템 프레임워크를 검증한 결과를 논의한다. Product regulations specify requirements or constraints for products that manufacturers must comply with across the entire product lifecycle, from design and manufacture, through operation and maintenance, to recycling and disposal. This paper suggests a system framework and its essential components for the verification of a pressure vessel design using the industrial standards of Korea. The authors also present methods to generate design template data from legacy design systems and to construct a regulation knowledge base. The proposed framework is demonstrated through experiments involving pressure vessel design verification using a prototype system.