• Title/Summary/Keyword: a fuzzy theory

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Evaluation of Risk Level for Damage of Marine Accidents In SRRs using Fuzzy Logic (퍼지로직을 이용한 해양사고 피해규모에 의한 해역별 위험수준 평가)

  • Jang Woon-Jae;Kwon Suk-Jae;Keum Jong-Soo
    • Proceedings of KOSOMES biannual meeting
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    • 2004.05b
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    • pp.1-6
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    • 2004
  • This paper suggests an evaluation of risk level for damage of marine accidents in SRRs. Qualitative analyses in words is sometimes priorior to quantative analyses in numeric symbols. This paper intoduces a concept of fuzzy theory with the plenty of related literature review and AHP in the Korean SRRs of RCC and RSC. The methodology of this paper is max . min composition of fuzzy extensive principle, defuzzifiation is centroid of gravity methods. At the result, the evaluation of risk level is especially over Serious for smarine accident of Taean, Gunsan, Mokpo, Yosu, Tongyoung, Busan SRR. This paper recommends that many Rescue Vessels and Equipments need to the reduction of risk level about those.

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Development of Traffic Accident Frequency Prediction Model in Urban Signalized Intersections with Fuzzy Reasoning and Neural Network Theories (퍼지 및 신경망이론을 이용한 도시부 신호교차로 교통사고예측모형 개발)

  • Kang, Young-Kyun;Kim, Jang-Wook;Lee, Soo-Il;Lee, Soo-Beom
    • International Journal of Highway Engineering
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    • v.13 no.1
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    • pp.69-77
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    • 2011
  • This study is to suggest a methodology to overcome the uncertainty and lack of reliability of data. The fuzzy reasoning model and the neural network model were developed in order to overcome the potential lack of reliability which may occur during the process of data collection. According to the result of comparison with the Poisson regression model, the suggested models showed better performance in the accuracy of the accident frequency prediction. It means that the more accurate accident frequency prediction model can be developed by the process of the uncertainty of raw data and the adjustment of errors in data by learning. Among the suggested models, the performance of the neural network model was better than that of the fuzzy reasoning model. The suggested models can evaluate the safety of signalized intersections in operation and/or planning, and ultimately contribute the reduction of accidents.

Multi-Objective Optimization of Steel Structures Using Fuzzy Theory (퍼지 이론을 이용한 강구조물의 다목적 최적설계)

  • Kim, Ki-Wook;Park, Moon-Ho
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.8 no.4
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    • pp.153-163
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    • 2004
  • The main objective of this study is to develop a multi-objective fuzzy optimum design program of steel structures and to verify that the multi-objective fuzzy optimum design is more reasonable than the single objective optimum design in real structural design. In the optimization formulation, the objective functions are both total weight and deflection. The design constraints are derived from the ultimate strength of service ability requirement of AISC-LRFD specification. The structural analysis was performed by the finite element method and also considered geometric non-linearity. The different importance of optimum criteria were reflected with two weighting methods ; membership weighting method and objective weighting method. Thus, designers could choose rational optimum solution of structures with application of two weighting methods.

Design of Fuzzy Pattern Classifier based on Extreme Learning Machine (Extreme Learning Machine 기반 퍼지 패턴 분류기 설계)

  • Ahn, Tae-Chon;Roh, Sok-Beom;Hwang, Kuk-Yeon;Wang, Jihong;Kim, Yong Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.5
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    • pp.509-514
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    • 2015
  • In this paper, we introduce a new pattern classifier which is based on the learning algorithm of Extreme Learning Machine the sort of artificial neural networks and fuzzy set theory which is well known as being robust to noise. The learning algorithm used in Extreme Learning Machine is faster than the conventional artificial neural networks. The key advantage of Extreme Learning Machine is the generalization ability for regression problem and classification problem. In order to evaluate the classification ability of the proposed pattern classifier, we make experiments with several machine learning data sets.

An Intelligent Self Health Diagnosis System using FCM Algorithm and Fuzzy Membership Degree (FCM 알고리즘과 퍼지 소속도를 이용한 지능형 자가 진단 시스템)

  • Kim, Kwang-Baek;Kim, Ju-Sung
    • Journal of Intelligence and Information Systems
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    • v.13 no.1
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    • pp.81-90
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    • 2007
  • This paper shows an intelligent disease diagnosis system for public. Our system deals with 30 diseases and their typical symptoms selected based on the report from Ministry of Health and Welfare, Korea. Technically, the system uses a modified FCM algorithm for clustering diseases and the input vector consists of the result of user-selected questionnaires. The modified FCM algorithm improves the quality of clusters by applying symmetrically measure based on the fuzzy theory so that the clusters are relatively sensitive to the shape of the pattern distribution. Furthermore, we extract the highest 5 diseases only related to the user-selected questionnaires based on the fuzzy membership function between questionnaires and diseases in order to avoid diagnosing unrelated disease.

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Design of the Model for Predicting Ship Collision Risk using Fuzzy and DEVS (퍼지와 DEVS를 이용한 선박 충돌 위험 예측 모델 설계)

  • Yi, Mira
    • Journal of the Korea Society for Simulation
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    • v.25 no.4
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    • pp.127-135
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    • 2016
  • Even thought modernized marine navigation devices help navigators, marine accidents has been often occurred and ship collision is one of the main types of the accidents. Various studies on the assessment method of collision risk have been reported, and studies using fuzzy theory are remarkable for the reason that reflect linguistic and ambiguous criteria for real situations. In these studies, collision risks were assessed on the assumption that the current state of navigation ship would be maintained. However, navigators ignore or turn off frequent alarms caused by the devices predicting collision risk, because they think that they can avoid the collisions in the most of situations. This paper proposes a model of predicting ship collision risk considering the general patterns of collision avoidance, and the approach is based on fuzzy inference and discrete event system specification (DEVS) formalism.

Intelligent Steering Control System Based on Voice Instructions

  • Seo, Ki-Yeol;Oh, Se-Woong;Suh, Sang-Hyun;Park, Gyei-Kark
    • International Journal of Control, Automation, and Systems
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    • v.5 no.5
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    • pp.539-546
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    • 2007
  • The important field of research in ship operation is related to the high efficiency of transportation, the convenience of maneuvering ships and the safety of navigation. For these purposes, many intelligent technologies for ship automation have been required and studied. In this paper, we propose an intelligent voice instruction-based learning (VIBL) method and discuss the building of a ship's steering control system based on this method. The VIBL system concretely consists of two functions: a text conversion function where an instructor's inputted voice is recognized and converted to text, and a linguistic instruction based learning function where the text instruction is understood through a searching process of given meaning elements. As a study method, the fuzzy theory is adopted to build maneuvering models of steersmen and then the existing LIBL is improved and combined with the voice recognition technology to propose the VIBL. The ship steering control system combined with VIBL is tested in a ship maneuvering simulator and its validity is shown.

Context-Aware Security System for the Smart Phone-based M2M Service Environment

  • Lee, Hyun-Dong;Chung, Mok-Dong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.1
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    • pp.64-83
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    • 2012
  • The number of smart phone users is rapidly growing due to recent increase in wireless Internet usage, development of a wide variety of applications, and activation of M2M (Machine to machine) services. Although the smart phone offers benefits of mobility and convenience, it also has serious security problems. To utilize M2M services in the smart phone, a flexible integrated authentication and access control facility is an essential requirement. To solve these problems, we propose a context-aware single sign-on and access control system that uses context-awareness, integrated authentication, access control, and an OSGi service platform in the smart phone environment. In addition, we recommend Fuzzy Logic and MAUT (Multi-Attribute Utility Theory) in handling diverse contexts properly as well as in determining the appropriate security level. We also propose a security system whose properties are flexible and convenient through a typical scenario in the smart phone environment. The proposed context-aware security system can provide a flexible, secure and seamless security service by adopting diverse contexts in the smart phone environment.

Risk Assessment of Marine LPG Engine Using Fuzzy Multicriteria HAZOP Technique (퍼지 다기준 HAZOP 기법을 이용한 해상용 LPG 엔진의 위험성 평가)

  • Siljung Yeo
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.2
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    • pp.238-247
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    • 2023
  • Liquefied petroleum gas (LPG) is an attractive fuel for ships considering its current technology and economic viability. However, safety guidelines for LPG-fueled ships are still under development, and there have been no cases of applying LPG propulsion systems to small and medium-sized ships in Korea. The purpose of this study was to perform an objective risk assessment for the first marine LPG engine system and propose safe operational standards. First, hazard and operability (HAZOP) analysis was used to divide the engine system into five nodes, and 58 hazards were identified. To compensate for the subjectivity of qualitative evaluation using HAZOP analysis, fuzzy set theory was used, and additional risk factors, such as detectability and sensitivity, were included to compare the relative weights of the risk factors using a fuzzy analytical hierarchy process. As a result, among the five risk factors, those with a major impact on risk were determined to be the frequency and severity. Finally, the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) was applied to select the risk rank more precisely by considering the weights of the risk factors. The risk level was divided into 47 groups, and the major hazard during the operation of the engine system was found through the analysis to be gas leakage during maintenance of the LPG supply line. The technique proposed can be applied to various facilities, such as LPG supply systems, and can be utilized as a standard procedure for risk assessment in developing safety standards for LPG-powered ships.

Automation of Analysis for Stress Intensity Factor of 3-D Cracks (3차원 균열의 응력확대계수에 대한 해석의 자동화)

  • 이준성
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1997.04a
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    • pp.496-500
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    • 1997
  • This paper describes an automated system for analyzing the stress intensity factors(SIFs) of three-dimensional (3D) cracks. A geometry model, i.e.a solid containing one or several 3D cracks is defined. Several distributions of local node density are chosen, and then automatically superposed on one another over the geometry model by using the fuzzy knowledge processing. Nodes are generated by the bucketing method, and ten-noded quadratic tetrahedral solid elements are generated by the Delauuay triangulation techniques. The singular elements such that the mid-point nodes near crack fornt are shifted at the quarter-points are automatically placed along the 3D crack front. THe complete finite element (FE) model generated, i.e the mesh with material properties and boundary conditions is given to one of the commercial FE codes, and a stress analysis is performed. The SIFs are calculated using the displacement extrapolation method. To demonstrate practical performance of the present system, a semi- elliptical surface crack in a plate subjected to tension is solved.

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