• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.49-55
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• 2019

In this paper, we propose ontology-based recommendation system for supporting maintenance of Korean architectural heritage. This study includes the following: 1) design of ontology expressing repair information of architectural heritage, 2) creation of repair case DB, 3) creation of a recommendation system of repair method. For this study, we designed the ontology that expresses the information of Korean wooden building cultural heritage by referring to the existing heritage ontologies. Second, we created the repair information database based on the repair contents and the expert interview data provided by the National Institute of Cultural Heritage and the Cultural Heritage Administration. Third, we developed a system that recommends the repair method of Korean wooden architectural heritage with the most similar phenomena and causes. This study contributes to sharing repair knowledge and determining repair methods for architectural heritage repair.

• Korean Journal of Construction Engineering and Management
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• v.10 no.4
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• pp.87-100
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• 2009

The quality of early cost estimates is critical to the feasibility analysis and budget allocation decisions for public capital projects. Various researches have been attempted to develop cost prediction models in the early stage of a construction project. However, existing studies are limited on its applicability to actual projects because they focus primarily on a specific phase as well as utilize restricted information while the amount of information collectable differs from one another along with the project stages. This research aims to develop two-staged cost estimation model for the schematic planning and preliminary design process of a construction projects, considering the available information of each phase. In the schematic planning stage where outlined information of a project is only available, the Case-Based Reasoning model is used for easy and rapid elicitation of a project cost based on the extensive database of more than 90 actual highway construction projects. Then, the representing quantity-based model is proposed for the preliminary design stage where more information on the quantities and unit costs are collectable based on the alternative routes and cross-sections of a highway project. Real case studies are used to demonstrate and validate the benefits of the proposed approach. Through the two-stage cost estimation system, users are able to hold a timely prospect to presume the final cost within the budge such that feasibility study as well as budget allocation decisions are made on effectively and competitively.

• Korean Journal of Construction Engineering and Management
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• v.12 no.1
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• pp.53-61
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• 2011

For construction projects, the importance of early cost estimates is highly recognized by the project team and sponsoring organization because early cost estimates are frequently a foundation of business decisions as well as a basis for identifying any changes as the project progresses from design to construction. However, it is difficult to accurately estimate construction cost in the early stage of a project due to various uncertainties in construction. To deal with these uncertainties, cost estimates should be made several times over the course of the project. In particular, early cost estimates are essential process for successful project management. For accurate construction cost estimates, it is necessary to compare cost estimates with actual costs based on historical project data. In this context, case-based reasoning (CBR), which is the process of solving new problems based on the solutions of similar past problems, can be considered as an effective method for cost estimating. To obtain this, it is also required to define the attribute similarities and the attribute weights. However, no existing method is capable of determining attribute weights of qualitative variables. Consequently, it has been a well-known barrier of accurate early cost estimates. Using Genetic Algorithms (GA), this research suggests the method of determining the attribute weight of qualitative variables. Based on building project case studies, the proposed methodology was validated.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.108-114
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• 2019

In this paper, we propose an intelligent vocabulary recommendation agent that automatically provides vocabulary corresponding to game-based learners' needs and requirements in the mobile education augmented reality game environment. The proposed agent reflects the characteristics of mobile technology and augmented reality technology as much as possible. In addition, this agent includes a vocabulary reasoning module, a single game vocabulary recommendation module, a battle game vocabulary recommendation module, a learning vocabulary list Module, and a thesaurus module. As a result, game-based learners' are generally satisfied. The precision of context vocabulary reasoning and thesaurus is 4.01 and 4.11, respectively, which shows that vocabulary related to situation of game-based learner is extracted. However, In the case of satisfaction, battle game vocabulary(3.86) is relatively low compared to single game vocabulary(3.94) because it recommends vocabulary that can be used jointly among recommendation vocabulary of individual learners.

• Journal of Korean Society of Transportation
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• v.14 no.1
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• pp.51-67
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• 1996

The optimal path-finding problem becomes complicated when multiple variables are simultaneously considered such as physical route length, degree of congestion, traffic capacity of intersections, number of intersections and lanes, and existence of free ways. Therefore, many researchers in various fields (management science, computer science, applied mathematics, production planning, satellite launching) attempted to solve the problem by ignoring many variables for problem simplification, by developing intelligent algorithms, or by developing high-speed hardware. In this research, an integration of expert system technique and case-based reasoning in high level with a conventional algorithms in lower level was attempted to develop an optimal path-finding system. Early application of experienced driver's knowledge and case data accumulated in case base drastically reduces number of possible combinations of optimal paths by generating promising alternatives and by eliminating non-profitable alternatives. Then, employment of a conventional optimization algorithm provides faster search mechanisms than other methods such as bidirectional algorithm and $A^*$ algorithm. The conclusion obtained from repeated laboratory experiments with real traffic data in Seoul metropolitan area shows that the integrated approach to finding optimal paths with consideration of various real world constraints provides reasonable solution in a faster way than others.

• Journal of the Society of Naval Architects of Korea
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• v.35 no.4
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• pp.109-117
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• 1998

In a preliminary design available information is limited, so it makes attractive to rely on the design cases of existing ships to design new ships. In this paper a prototype of the case-based conceptual design system of a ship is developed to support systematically the design process. This system not only generates design candidates through a case indexing, but also determines the priorities of the candidates by using nearest neighbor matching algorithm. The final solution is presented through adaptation process. The validation of the system was examined and verified by applying to conceptual ship design stage.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.39-44
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• 2006

Ship's collision avoidance is a skill that masters of merchant marine vessels have acquired through years of experience and that makes them feel at ease to guide their ship out from danger quickly compared to inexperienced officers. Case based reasoning(CBR) uses the same technique in solving tasks that needs reference from variety of situations. CBR can render decision-making easier by retrieving past solutions from situations that are similar to the one at hand and make necessary adjustments in order to adapt them. In this paper, we propose to utilize the advantages of CBR in a support system for ship's collision avoidance while using fuzzy algorithm for its retrieval of similar navigational situations, stored in the casebase, thus avoiding the cumbersome tasks of creating a new solution each time a new situation is encountered. There will be two levels within the Fuzzy-CBR. The first level will identify the dangerous ships and index the new case. The second level will retrieve cases from casebase and adapt the solution to solve for the output. While CBR's accuracy depends on the efficient retrieval of possible solutions to be adapted from stored cases, fuzzy algorithm will improve the effectiveness of solving the similarity to a new case at hand.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.433-436
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• 2002

본 논문은 인터넷상에서 전자우편물을 자동으로 생성하기 위한 에이전트에 관한 연구로서, 사례기반추론(Case-Based Reasoning:CBR) 모델을 통하여 우편물 발송자의 특성에 적응하는 에이전트의 설계 방안을 제안한다. 먼저, 지능형 에이전트와 사례기반 추론에 관하여 간략하게 조사한 후, 전자우편분석 에이전트, 색인 에이전트, 검색엔진 등으로 구성되는 다중 에이전트 시스템을 보여준다. 특히, 인공지능 기법 중의 하나인 사례기반추론의 유사도 계산 방식과 새로운 CBR 처리주기를 이용하여 전자우편물을 자동으로 생성하는 에이전트 시스템을 제안한다. 그리고 Databases와 Case-Bases를 설명하고 전자우편 자동생성 에이전트를 위한 CBR 처리주기를 제안한다. 그 다음, 에이전트와 사례 연구를 위한 프로토타입을 제공한다. 향후, Data-Mining 기법의 연구는 이 시스템이 사용자의 다양한 취향에 적응할 수 있는 유용한 시스템으로 발전하는데 도움이 될 것이다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.05a
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• pp.333-341
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• 2002

사례기반추론기법을 통한 유사상품의 탐색과 사용자 요구에 적합한 상품추천을 위해서는 다양한 요구에 부응할 수 있는 사례베이스의 구축이 우선되어야 한다 이에 본 연구에서는 인터넷 쇼핑몰의 상품추천시스템에서 번들상품구성문제를 표현하는데 적합한 사례표현기법을 개발하며, 유1.1사례를 추출하기 위한 유사도 척도의 개발에 연구의 첫 번째 주안점을 둔다. 본 논문에서는 번들상품추천을 위한 사례표현기법으로 속성-값(feature-value) 방식인 프레임(frame) 형식을 사용하고 있다 또한 유사도 측정을 위하여 각 속성(행사, 예산, 참여자 수, 고객 거주지 등)에 대하여 유사도 테이블을 작성하고, 이들 속성들의 가중합계방법을 이용하고 있다.

• Journal of Korean Society for Quality Management
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• v.19 no.1
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• pp.151-162
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• 1991

The purpose of this study is to propose a facility layout design algorithm based on artificial intelligence concept, and then to develop a computer program which is more practical than any other conventional facility layout design systems. The algorithm is composed of five step layout procedures; knowledge and data input, knowledge interpretation, priority determination, inference of layout design, and evaluation, In the step of priority determination, the algorithm is divided into single row and multi row layout problem. In the step of inference of layout design, alternatives are generated by constraints-directed reasoning and depth first search method based on artificial intelligence concept. Alternatives are evaluated by the moving cost and relationship value by interactive man-machine interface in the step of evaluation. As a case study, analytical considerations over conventional programs such as CRAFT and CORELAP was investigated and compared with algorithm propsed in this study. The proposed algorithm in this study will give useful practical tool for layout planner. The computer progran was written in C language for IBM PC-AT.