• Title/Summary/Keyword: fuzzy extension

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A NOTE ON THE MAXIMUM ENTROPY WEIGHTING FUNCTION PROBLEM

  • Hong, Dug-Hun;Kim, Kyung-Tae
    • Journal of applied mathematics & informatics
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    • v.23 no.1_2
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    • pp.547-552
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    • 2007
  • In this note, we extends some of the results of Liu [Fuzzy Sets and systems 157 (2006) 869-878]. This extension consists of a simple proof involving weighted functions and their preference index. We also give an elementary simple proof of the maximum entropy weighting function problem with a given preference index value without using any advanced theory like variational principles or without using Lagrangian multiplier methods.

Design and Fabrication of Ballast Water Treatment System using Fuzzy PID Controller (퍼지 PID 제어 기법을 이용한 선박평형수 처리 시스템 설계 및 제작)

  • Lee, Young-Dong;Ahn, Byeong-Gu;Noh, Yun-Hong;Jeong, Do-Un
    • Journal of the Institute of Convergence Signal Processing
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    • v.16 no.3
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    • pp.108-114
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    • 2015
  • Ballast water is carried by ships to ensure stability, trim and structural integrity. When a ship loads cargo, the ballast water is discharged. When foreign marine microorganisms are introduced into new marine environments, they pose a threat to the local marine ecological system. UV system is commonly used for the disinfection of waste and surface water. This method would not be as efficient because some species do survive to form viable populations, much of the sediment and organisms at the bottom of tanks, and may become serious pests. In this paper, we designed and implemented ballast water treatment system using fuzzy PID controller to prevent lamp damage, and to reduce the formation of the viable populations. The experiments were conducted with ballast water treatment system using fuzzy PID controller with short time exposure to the temperature above $40^{\circ}C$. This system was shown to be effective by significantly reducing bacterial population and lamp life extension through appropriate temperature of ballast water.

Evaluation of Risk Level for Damage of Marine Accidents in SRRs using Inner-Outer Dependence Method (내부-외부 종속법을 이용한 수색.구조 구역의 위험성 평가)

  • Jang, Woon-Jae;Keum, Jong-Soo
    • Proceedings of KOSOMES biannual meeting
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    • 2006.05a
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    • pp.59-64
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    • 2006
  • In this study, the risk of SRRs was assessed upon the scale of the damage of marine accidents. For the risk assessment, inner-outer dependence methods and special knowledge-based fuzzy logic were introduced. Also, in order to calculate the importance of assessment value in this study, a max min composition method was used for fuzzy logic based on the principle of fuzzy extension and the centroid of gravity method was used for non-fuzzy formation. In order to produce the importance of assessment items, the inner-outer dependence methods were used for assessment items, and markov analysis method was used for the importance of the final comprehensive assessment. As a result, the risk of SRR of Tongyoung and Yeosu was proven relatively higher, thus, it needs to have more rescue ships and rescue devices for relieving the risk in the future.

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A Fuzzy Traffic Controller with Asymmetric Membership Functions (비대칭적인 소속 함수를 갖는 퍼지 교통 제어기)

  • Kim, Jong-Wan;Choi, Seung-Kook
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.10
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    • pp.2485-2492
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    • 1997
  • Nowadays the traffic conditions have been getting worse due to continuous increase in the number of vehicles. So it has become more important to manage traffic signal lights efficiently. Recently fuzzy logic is introduced to control the cycle time of traffic lights adaptively. Conventional fuzzy logic controller adjusts the extension time of current green phase by using the fuzzy input variables such as the number of entering vehicles at the green light and the number of waiting vehicle during the red light. However this scheme is inadequate for an intersection with variable traffic densities. In this paper, a new FLC with asymmetric membership functions that reflects more exactly traffic flows than other FLCs with symmetric ones regardless of few control rules is propsed. The effectiveness of the proposed method was shown through simulation of a single intersection. The experimental results yielded the superior performance of the proposed FLC in terms of the average delay time, the number of passed vehicles, and the degree of saturation.

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Evaluation of Risk Level for Damage of Marine Accidents in SRRs using Inner-Outer Dependence Method (내부-외부 종속법을 이용한 수색.구조 구역의 위험성 평가)

  • Jang Woon-Jae;Keum Jong-Soo
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.12 no.3 s.26
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    • pp.219-224
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    • 2006
  • In this study, the risk of SRRs was assessed upon the scale of the damage of marine accidents. For the risk assessment, inner-outer dependence methods and special knowledge-based fuzzy logic were introduced. Also, in order to calculate the importance of assessment value in this study, a max-min composition method was used for fuzzy logic based on the principle of fuzzy extension and the centroid of gravity method was used for non-fuzzy formation. In order to produce the importance of assessment items, the inner-outer dependence methods were used for assessment items, and markov analysis method was used for the importance of the final comprehensive assessment. As a result, the risk of SRR of Tongyoung, Mokpo and Yeosu was proven relatively higher, thus, it needs to have more rescue ships and rescue devices for relieving the risk in the future.

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Fuzzy Inference System Architecture for Customer Satisfaction Service (고객 만족 서비스를 위한 퍼지 추론 시스템 구조)

  • Kwon, Hee-Chul;Yoo, Jung-Sang
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.1
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    • pp.219-226
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    • 2010
  • Recently most parking control systems provide customers with various services, but most of the services are just the extension of parking spaces, automatic parking control system and so on. It is essential to use the satisfaction degree as the extent that customer are satisfied with parking control system to improve the quality of the system services and diversify the system services. The degree of satisfaction is different from customer to customer in same condition and can be represented as linguistic variables. In this paper, we present therefore a technique that quantify how much customer are satisfied with parking control system and fuzzy inference system architecture as a solution that can help us to make a efficient decision for these parking problems. In this architecture, inference engine using fuzzy logic compares context data with the rules in the fuzzy rule-based system, gets the sub-results, aggregates them and defuzzifies the aggregated result using MATLAB application programming to obtain crisp value. Fuzzy inference system architecture presented in this paper, can be used as a efficient method to analyze the satisfaction degree which is represented as fuzzy linguistic variables by human emotion. And it can be used to improve the satisfaction degree of not only parking system but also other service systems of various domains.

Discriminant analysis based on a calibration model (Calibration 모형을 이용한 판별분석)

  • 이석훈;박래현;복혜영
    • The Korean Journal of Applied Statistics
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    • v.10 no.2
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    • pp.261-274
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    • 1997
  • Most of the data sets to which the conventional discriminant rules have been applied contain only those which belong to one and only one class among the classes of interest. However the extension of the bivalence to multivlaence like Fuzzy concepts strongly influence the traditional view that an object must belong to only class. Thus the goal of this paper is to develop new discriminant rules which can handle the data each object of which may belong to moer than two classes with certain degrees of belongings. A calibration model is used for the relationship between the feature vector of an object and the degree of belongings and a Bayesian inference is made with the Metropolis algorithm on the degree of belongings when a feature vector of an object whose membership is unknown is given. An evalution criterion is suggested for the rules developed in this paper and comparision study is carried using two training data sets.

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Development of Fuzzy Control Method Powered Gait Orthosis for Paraplegic Patients (하반신 마비환자를 위한 동력보행보조기의 퍼지제어 기법 개발)

  • Kang, Sung-Jae;Ryu, Jei-Cheong;Kim, Gyu-Suk;Kim, Young-Ho;Mun, Mu-Seong
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.2
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    • pp.163-168
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    • 2009
  • In this study, we would be developed the fuzzy controlled PGO that controlled the flexion and the extension of each PGO's hip joint using the bio-signal and FSR sensor. The PGO driving system is to couple the right and left sides of the orthosis by specially designed hip joints and pelvic section. This driving system consists of the orthosis, sensor, control system. An air supply system of muscle is composed of an air compressor, 2-way solenoid valve (MAC, USA), accumulator, pressure sensor. Role of this system provide air muscle with the compressed air at hip joint constantly. According to output signal of EMG sensor and foot sensor, air muscles and assists the flexion of hip joint during PGO gait. As a results, the maximum hip flexion angles of RGO's gait and PGO's gait were about $16^{\circ}\;and\;57^{\circ}$ respectively. The maximum angle of flexion/extention in hip joint of the patients during RGO's gait are smaller than normal gait, because of the step length of them shoes a little bit. But maximum angle of flexion/extention in hip joint of the patients during PGO's gait are larger than normal gait.

AutoScale: Adaptive QoS-Aware Container-based Cloud Applications Scheduling Framework

  • Sun, Yao;Meng, Lun;Song, Yunkui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.6
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    • pp.2824-2837
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    • 2019
  • Container technologies are widely used in infrastructures to deploy and manage applications in cloud computing environment. As containers are light-weight software, the cluster of cloud applications can easily scale up or down to provide Internet-based services. Container-based applications can well deal with fluctuate workloads by dynamically adjusting physical resources. Current works of scheduling applications often construct applications' performance models with collected historical training data, but these works with static models cannot self-adjust physical resources to meet the dynamic requirements of cloud computing. Thus, we propose a self-adaptive automatic container scheduling framework AutoScale for cloud applications, which uses a feedback-based approach to adjust physical resources by extending, contracting and migrating containers. First, a queue-based performance model for cloud applications is proposed to correlate performance and workloads. Second, a fuzzy Kalman filter is used to adjust the performance model's parameters to accurately predict applications' response time. Third, extension, contraction and migration strategies based on predicted response time are designed to schedule containers at runtime. Furthermore, we have implemented a framework AutoScale with container scheduling strategies. By comparing with current approaches in an experiment environment deployed with typical applications, we observe that AutoScale has advantages in predicting response time, and scheduling containers to guarantee that response time keeps stable in fluctuant workloads.

Construction of MATLAB API for Fuzzy Expert System Determining Automobile Warranty Coverage (자동차 보증수리 기간 결정을 위한 퍼지 전문가 시스템용 MATLAB API의 구축)

  • Lee, Sang-Hyoun;Kim, Chul-Min;Kim, Byung-Ki
    • The KIPS Transactions:PartD
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    • v.12D no.6 s.102
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    • pp.869-874
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    • 2005
  • In the recent years there has been an increase of service competition in the activity of product selling, especially in the extension of warranty coverage and qualify. The variables in connection with the service competition are not crisp, and required the expertise of the production line. It thus becomes all the more necessary to use subtler tools as decision supports. These problems are typical not only of product companies but also of financial organizations, credit institutions, insurance, which need predictions of credibility for firms or persons in which they have any kind of interest. A suitable approach for minimizing the risk is to use a knowledge-based system. Most often expert systems are not standalone programs, but are embedded into a larger application. The aim of this paper is to discuss an approach for developing an embedded fuzzy expert system with respect to the product selling policy, especially to present the decision system of automobile selling activity around the extension of warranty coverage and quality. We use the MATLAB tools which integrates computation, visualization, and programming in an easy-to-use environment where problems and solutions are expressed in familiar mathematical notation. Also, we present the API functions embedding into the existing application.