• Title/Summary/Keyword: Fuzzy Decision Making

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A Ranking Method of Fuzzy Numbers based on Users'Preference and its Application to Decision Making (사용자의 선호도를 반영하는 퍼지숫자의 정렬 방법 및 의사결정에의 응용)

  • Lee, Ji-Hyeong;Lee, Gwang-Hyeong
    • Journal of KIISE:Software and Applications
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    • v.26 no.3
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    • pp.441-451
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    • 1999
  • 본 논문에서는 퍼지숫자를 정렬하는 새로운 방법을 제안한다. 제안하는 방법은 사용자의 관심도나 선호도를 반영할 수 있는 방법을 제공하며, 퍼지숫자의 전체적인 가능성분포를 고려하는 평가함수를 방법은 사용자가 제사한 퍼지 집합과 만족도 함수(satisfaction fuction)를 이용하여 정렬 대상이 되는 퍼지숫자를 평가한 후 그 평가값에 따라서 순위를 정하게 된다. 만족도 함수는 두 퍼지숫자의 비교를 위해서 이전에 제안된 방법으로 퍼지숫자의 전체적인 가능성을 고려하는 특징이 있다. 본 논문에서는 제안하는 방법을 퍼지숫자 정렬에 적용한 예와 기존의 방법과 비교한 결과를 보이며, 응용 예로서 의사결정의 문제에 적용한 결과를 제시한다.

Application of the auxiliary tunnel reinforcement design using the decision making tools based on expert system integrated fuzzy inference rule

  • Kim Changyong;Hong Sungwan;Bae Gyujin;Kim Kwangyeom
    • 한국지구물리탐사학회:학술대회논문집
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    • 2003.11a
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    • pp.262-271
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    • 2003
  • Specification of reinforcement method was suggested according to the ground condition and tunnelling environment such as adjacent building and surface settlement. Tunnel database consists of 8 different groups of data according to the tunnel construction situations and major problems of ground. A tunnel countermeasure expert system based on client/server system was developed with on-line. The expert system provides proper solution to the each construction sites backing up the information of the tunnelling and ground information through Internet. The effective factors of tunnel construction were shown by the analyzing relationship and partial relationship between face stability and RMR factors. This study will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system escaping from the dependence of some experienced experts for the absent of guide.

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Mobile Tracking Method based on the Fuzzy Mliti-criteria Decision Making (퍼지 다기준 의사 결정을 이용한 이동체 위치 추적 방법)

  • 이기성;신창둔;이종찬;이근왕
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.7A
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    • pp.1144-1151
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    • 2001
  • 본 연구에서는 AOA(Angle of Arrival)와 TOA(Time of Arrival) 그리고 TDOA(Time Difference of Arrival)의 추정값을 이용한 위치 추정 기법들이 설명되고 분석된다. 이들 기법들을 다중경로 페이딩 (mutipath fading)과 shadowing을 갖는 마이크로셀 환경에 적용한다면, 빠르고 예측할 수 없는 신호 레벨의 변화로 인하여 이동체의 위치를 정확히 추정하는 것은 어렵다. 따라서 본 연구에서는 수신 신호 세기(RSS: Received Signal Strength) 이외에 이동체와 기지국간의 거리, 이동체의 이동방향, 이동체의 이전위치와 같은 부정확한 다수의 파라미터를 동시에 고려하는 퍼지 다기준 (multi-criteria) 의사 결정 방법을 이용하여 이동체의 위치를 결정하는 방법을 제안한다. 시뮬레이션을 통하여, 이동체의 방향과 속도의 영향을 분석한다.

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Knowledge-Based Dynamic Structuring of Process Control Systems

  • de Silba, Clarence W.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1137-1140
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    • 1993
  • A dynamic-structure system is one that has the flexibility to change the system configuration automatically so as to operate in an optimal manner. A conceptural model for a dynamic-structure system is presented in this paper. In this model, the interchangeable components of the overall system are grouped together. Their activity levels are evaluated by an intelligent preprocessor that is associated with the group. A knowledge-based task distribution system evaluates the activity levels and makes decisions as to how the components operating below capacity should be shared with workcells that have similar components that are overloaded. Associated decision making can be effected through fuzzy logic and particularly the compositional rule of inference. A simulation example is given to illustrate the application of dynamic structuring.

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Application of Artificial Intelligence for the Management of Oral Diseases

  • Lee, Yeon-Hee
    • Journal of Oral Medicine and Pain
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    • v.47 no.2
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    • pp.107-108
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    • 2022
  • Artificial intelligence (AI) refers to the use of machines to mimic intelligent human behavior. It involves interactions with humans in clinical settings, and augmented intelligence is considered as a cognitive extension of AI. The importance of AI in healthcare and medicine has been emphasized in recent studies. Machine learning models, such as genetic algorithms, artificial neural networks (ANNs), and fuzzy logic, can learn and examine data to execute various functions. Among them, ANN is the most popular model for diagnosis based on image data. AI is rapidly becoming an adjunct to healthcare professionals and is expected to be human-independent in the near future. The introduction of AI to the diagnosis and treatment of oral diseases worldwide remains in the preliminary stage. AI-based or assisted diagnosis and decision-making will increase the accuracy of the diagnosis and render treatment more precise and personalized. Therefore, dental professionals must actively initiate and lead the development of AI, even if they are unfamiliar with it.

A Utility Evaluation Framework of Blockchain Services using a MCDM (다중의사결정모델을 이용한 블록체인 서비스 효용 평가 프레임워크)

  • Kwang-Kyu Seo
    • Journal of the Semiconductor & Display Technology
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    • v.23 no.2
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    • pp.45-49
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    • 2024
  • Blockchain has gone beyond the proof-of-concept level and is converging with various industries and fields, moving toward the service development and commercialization stage. However, although various blockchain technologies and services are emerging, their development is quite slow and their widespread application to various industries is difficult. Accordingly, it is necessary to identify areas with high introduction utility when applying blockchain services in actual industries and to develop a method to evaluate the utility of blockchain services for this purpose. This paper proposes a framework for evaluating the utility of blockchain services using a multi-criteria decision-making model. Through a case study on the utility evaluation of blockchain services, the proposed framework was applied to domestic and foreign blockchain services to evaluate its utility and verify its applicability. It is expected that the proposed framework will be able to identify industrial and functional characteristics where actual blockchain services can be introduced and demonstrate effective utility and can be used to develop blockchain services in various industrial fields.

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Prioritizing the locations for hydrogen production using a hybrid wind-solar system: A case study

  • Mostafaeipour, Ali;Jooyandeh, Erfan
    • Advances in Energy Research
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    • v.5 no.2
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    • pp.107-128
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    • 2017
  • Energy is a major component of almost all economic, production, and service activities, and rapid population growth, urbanization and industrialization have led to ever growing demand for energy. Limited energy resources and increasingly evident environmental effects of fossil fuel consumption has led to a growing awareness about the importance of further use of renewable energy sources in the countries energy portfolio. Renewable hydrogen production is a convenient method for storage of unstable renewable energy sources such as wind and solar energy for use in other place or time. In this study, suitability of 25 cities located in Iran's western region for renewable hydrogen production are evaluated by multi-criteria decision making techniques including TOPSIS, VIKOR, ELECTRE, SAW, Fuzzy TOPSIS, and also hybrid ranking techniques. The choice of suitable location for the centralized renewable hydrogen production is associated with various technical, economic, social, geographic, and political criteria. This paper describes the criteria affecting the hydrogen production potential in the study region. Determined criteria are weighted with Shannon entropy method, and Angstrom model and wind power model are used to estimate respectively the solar and wind energy production potential in each city and each month. Assuming the use of proton exchange membrane electrolyzer for hydrogen production, the renewable hydrogen production potential of each city is then estimated based on the obtained wind and solar energy generation potentials. The rankings obtained with MCDMs show that Kermanshah is the best option for renewable hydrogen production, and evaluation of renewable hydrogen production capacities show that Gilangharb has the highest capacity among the studied cities.

Structural monitoring of movable bridge mechanical components for maintenance decision-making

  • Gul, Mustafa;Dumlupinar, Taha;Hattori, Hiroshi;Catbas, Necati
    • Structural Monitoring and Maintenance
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    • v.1 no.3
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    • pp.249-271
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    • 2014
  • This paper presents a unique study of Structural Health Monitoring (SHM) for the maintenance decision making about a real life movable bridge. The mechanical components of movable bridges are maintained on a scheduled basis. However, it is desired to have a condition-based maintenance by taking advantage of SHM. The main objective is to track the operation of a gearbox and a rack-pinion/open gear assembly, which are critical parts of bascule type movable bridges. Maintenance needs that may lead to major damage to these components needs to be identified and diagnosed timely since an early detection of faults may help avoid unexpected bridge closures or costly repairs. The fault prediction of the gearbox and rack-pinion/open gear is carried out using two types of Artificial Neural Networks (ANNs): 1) Multi-Layer Perceptron Neural Networks (MLP-NNs) and 2) Fuzzy Neural Networks (FNNs). Monitoring data is collected during regular opening and closing of the bridge as well as during artificially induced reversible damage conditions. Several statistical parameters are extracted from the time-domain vibration signals as characteristic features to be fed to the ANNs for constructing the MLP-NNs and FNNs independently. The required training and testing sets are obtained by processing the acceleration data for both damaged and undamaged condition of the aforementioned mechanical components. The performances of the developed ANNs are first evaluated using unseen test sets. Second, the selected networks are used for long-term condition evaluation of the rack-pinion/open gear of the movable bridge. It is shown that the vibration monitoring data with selected statistical parameters and particular network architectures give successful results to predict the undamaged and damaged condition of the bridge. It is also observed that the MLP-NNs performed better than the FNNs in the presented case. The successful results indicate that ANNs are promising tools for maintenance monitoring of movable bridge components and it is also shown that the ANN results can be employed in simple approach for day-to-day operation and maintenance of movable bridges.

An Improved Handover Method Using Mobile Tracking by Fuzzy Multi-Criteria Decision Making (기준 의사 결정에 의한 모바일 트래킹을 이용한 향상된 핸드오버)

  • Kang, Il-Ko;Shin, Seong-Yoon;Lee, Jong-Chan;Pyo, Seong-Bae;Rhee, Yang-Won
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.3
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    • pp.1-10
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    • 2006
  • It is widely accepted that the coverage with high user densities can only be achieved with small cell such as micro- and pico-cell. The smaller cell size causes frequent handovers between cells and a decrease in the permissible handover Processing delay. This may result in the handover failure. in addition to the loss of some Packets during the handover. In these cases. re-transmission is needed in order to compensate errors, which triggers a rapid degradation of throughput. In this paper, we propose a new handover scheme in the next generation mobile communication systems, in which the handover setup process is done in advance before a handover request by predicting the handover cell based on mobile terminal's current position and moving direction. Simulation is focused on the handover failure rate and Packet loss rate. The simulation results show that our proposed method provides a better performance than the conventional method.

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A study on Operation factors the Used automobile logistics complex using Fuzzy-AHP (Fuzzy-AHP를 활용한 인천항 중고자동차 물류단지 운영 성공요인에 대한 연구)

  • Kim, Byung-Hwa;Cha, Young-Doo;Ma, Hye-Min;Yeo, Gi-Tae
    • Journal of Digital Convergence
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    • v.15 no.7
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    • pp.97-109
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    • 2017
  • Domestic vehicle penetration rate is growing at 3% per year, but consumers are increasingly buying used cars due to steady price hikes Nevertheless, the used car export market is expected to decline due to import regulations of major countries and the low grade environment of Used car export complex. Therefore, this study using Fuzzy-AHP was aimed to find operational factors of Used car logistics complex and establish a practical management plan of Used car logistic complex in incheon port. Fuzzy-AHP is the method that can be calculated weight of multi-level criteria and change linguistic ambiguity of human to Fuzzy Number. So it's able to propose the realistic decision making alternatives. As a result of the literacture reviews, present study focused on the analysis of the present situation of the logistics of the used car and the activation of the complex, suggested the activation plan and activation of the logistics complex. In the analysis of operational factors, logistic complex cost factors were found to be the most important factors by recording the weighted value of 0.306 in the above factors. The detailed factors were as follows: rent, accessibility, and logistics site size. It is necessary to compute competitive rent for the highly-advanced used car logistics complex, and to realize the rental support policy and to consider designating the free trade zone. In addition, it is necessary to expand the access infrastructure and secure the scale of the company for overseas buyers, and it is necessary to improve the overall government laws and introduce IT system for the future.