• Title/Summary/Keyword: Fuzzy sequence

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A Study on the Technique of Fault Classification in Transmission Lines Using a Combined Adaptive Network-Based Fuzzy Inference System (ANFIS를 이용한 송전선로의 고장판별 기법에 관한 연구)

  • Yeo, Sang-Min;Kim, Cheol-Hwan
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.50 no.9
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    • pp.417-423
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    • 2001
  • This paper proposes a technique for fault detection and classification for both LIF(Low Impedance Fault)s and HIF(High Impedance Fault)s using Adaptive Network-based Fuzzy Inference System(ANFIS). The inputs into ANFIS are current signals only based on Root-Mean-Square(RMS) values of 3-phase currents and zero sequence current. The performance of the proposed technique is tested on a typical 154 kV Korean transmission line system under various fault conditions. Test results show that the ANFIS can detect and classily faults including (LIFs and HIFs) accurately within half a cycle.

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NEW KINDS OF CONTINUITY IN FUZZY NORMED SPACES

  • Hazarika, Bipan;Mohiuddine, S.A.
    • Honam Mathematical Journal
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    • v.43 no.3
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    • pp.547-559
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    • 2021
  • We first define the notions of filter continuous, filter sequentially continuous and filter strongly continuous in the framework of fuzzy normed space (FNS), and then we introduce the notion of filter slowly oscillating sequences in the setting of FNS and shows that this notion is stronger than slowly oscillating sequences. Further, we define the concept of filter slowly oscillating continuous functions, filter Cesàro slowly oscillating sequences as well as some other related notions in the aforementioned space and investigate several related results.

Generalized Common Fixed Point Theorems on Menger PM-spaces

  • Lee, Byung-Soo;Yang, Kyu-Han
    • Journal of the Korean Institute of Intelligent Systems
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    • v.10 no.3
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    • pp.228-231
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    • 2000
  • More generalized common fixed point theorems for a sequence of fuzzy mappings to the nonexpansive case on Menger probabilistic metric spaces, which generalize recent results of Lee et al.[13], are obtained.

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A Study on the Algorithm for Fault Discrimination in Transmission Lines using Advanced Computational Intelligence(ACI) (ACI 기법을 이용한 송전선로 고장 종류 판별에 관한 연구)

  • Park Jae Hong;Lee Jong Beom
    • Proceedings of the KIEE Conference
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    • summer
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    • pp.619-621
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    • 2004
  • This paper presents the rapid and accurate algorithm for fault discrimination in transmission lines. When faults occur in transmission lines, fault discrimination is very important. If high impedance faults occur in transmission lines, it cannot be detected by overcurrent relays. The method using current and voltage cannot discriminate high impedance fault. Because of this reason this paper uses voltage and zero sequence current, and the proposed algorithm uses fuzzy logic method. This algorithm uses voltage and zero sequence current per period in case of faults. Single line ground fault and three-phase fault can be detective using voltage. Two-line ground fault and line to line fault and high impedance can be detected using zero sequence current. To prove the performance of the algorithm, it test algorithm with signal obtained from ATPDraw simulation.

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Negative Selection Algorithm for DNA Sequence Classification

  • Lee, Dong Wook;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.2
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    • pp.231-235
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    • 2004
  • According to revealing the DNA sequence of human and living things, it increases that a demand on a new computational processing method which utilizes DNA sequence information. In this paper we propose a classification algorithm based on negative selection of the immune system to classify DNA patterns. Negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes n group of antigenic receptor for n different patterns, they can classify into n patterns. In this paper we propose a pattern classification algorithm based on negative selection in nucleotide base level and amino acid level.

A study on the development of an arc sensor and its interface system for a welding robot (용접로봇을 위한 아크센서 및 인?이스 시스템 개발에 관한 연구)

  • 배강열;이지형;정창욱
    • Journal of Welding and Joining
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    • v.16 no.3
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    • pp.129-140
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    • 1998
  • An interface system was developed to offer the welding capability to a robot controller which had not any embedded function for arc welding before, and also an arc sensor algorithm was proposed for weld seam tracking of the welding robot. For the interface system between the robot controller and welding equipments, data communication software and interface connections were composed. The interface system was mae to correspond welding condition, correction data, operation sequence and current status with the robot controller by mutual had shaking and digital signal transfer. Graphic user interface program developed under the environment of windows made it easy to monitor data communication and operation status, and to control welding and sensing sequence. Arc sensing algorithm proposed in this study to compensate torch position error was based on a fuzzy logic with the variables of current difference and current differenced change at torch weaving extremities. The developed interface system could be successfully implemented in between welding equipments and the robot controller, and showed normal status and exact function in data and signal communication between the systems. The whole robot welding system was then examined to verify its welding and seam tracking capabilities in horizontal fillet, vertical fillet, and 3-dimensional fillet weldment. The experiments revealed sound weld bead shapes and also good seam tracing results.

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Design of a Recognizing System for Vehicle's License Plates with English Characters

  • Xing, Xiong;Choi, Byung-Jae;Chae, Seog;Lee, Mun-Hee
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.9 no.3
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    • pp.166-171
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    • 2009
  • In recent years, video detection systems have been implemented in various infrastructures such as airport, public transportation, power generation system, water dam and so on. Recognizing moving objects in video sequence is an important problem in computer vision, with applications in several fields, such as video surveillance and target tracking. Segmentation and tracking of multiple vehicles in crowded situations is made difficult by inter-object occlusion. In the system described in this paper, the mean shift algorithm is firstly used to filter and segment a color vehicle image in order to get candidate regions. These candidate regions are then analyzed and classified in order to decide whether a candidate region contains a license plate or not. And then some characters in the license plate is recognized by using the fuzzy ARTMAP neural network, which is a relatively new architecture of the neural network family and has the capability to learn incrementally unlike the conventional BP network. We finally design a license plate recognition system using the mean shift algorithm and fuzzy ARTMAP neural network and show its performance via some computer simulations.

Pathway Retrieval for Transcriptome Analysis using Fuzzy Filtering Technique andWeb Service

  • Lee, Kyung-Mi;Lee, Keon-Myung
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.2
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    • pp.167-172
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    • 2012
  • In biology the advent of the high-throughput technology for sequencing, probing, or screening has produced huge volume of data which could not be manually handled. Biologists have resorted to software tools in order to effectively handle them. This paper introduces a bioinformatics tool to help biologists find potentially interesting pathway maps from a transcriptome data set in which the expression levels of genes are described for both case and control samples. The tool accepts a transcriptome data set, and then selects and categorizes some of genes into four classes using a fuzzy filtering technique where classes are defined by membership functions. It collects and edits the pathway maps related to those selected genes without analyst' intervention. It invokes a sequence of web service functions from KEGG, which an online pathway database system, in order to retrieve related information, locate pathway maps, and manipulate them. It maintains all retrieved pathway maps in a local database and presents them to the analysts with graphical user interface. The tool has been successfully used in identifying target genes for further analysis in transcriptome study of human cytomegalovirous. The tool is very helpful in that it can considerably save analysts' time and efforts by collecting and presenting the pathway maps that contain some interesting genes, once a transcriptome data set is just given.

Hybrid Fuzzy PI-Control Scheme for Quasi Multi-Pulse Interline Power Flow Controllers Including the P-Q Decoupling Feature

  • Vural, Ahmet Mete;Bayindir, Kamil Cagatay
    • Journal of Power Electronics
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    • v.12 no.5
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    • pp.787-799
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    • 2012
  • Real and reactive power flows on a transmission line interact inherently. This situation degrades power flow controller performance when independent real and reactive power flow regulation is required. In this study, a quasi multi-pulse interline power flow controller (IPFC), consisting of eight six-pulse voltage source converters (VSC) switched at the fundamental frequency is proposed to control real and reactive power flows dynamically on a transmission line in response to a sequence of set-point changes formed by unit-step reference values. It is shown that the proposed hybrid fuzzy-PI commanded IPFC shows better decoupling performance than the parameter optimized PI controllers with analytically calculated feed-forward gains for decoupling. Comparative simulation studies are carried out on a 4-machine 4-bus test power system through a number of case studies. While only the fuzzy inference of the proposed control scheme has been modeled in MATLAB, the power system, converter power circuit, control and calculation blocks have been simulated in PSCAD/EMTDC by interfacing these two packages on-line.

Fragment Combination From DNA Sequence Data Using Fuzzy Reasoning Method (퍼지 추론기법을 이용한 DNA 염기 서열의 단편결합)

  • Kim, Kwang-Baek;Park, Hyun-Jung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.12
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    • pp.2329-2334
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    • 2006
  • In this paper, we proposed a method complementing failure of combining DNA fragments, defect of conventional contig assembly programs. In the proposed method, very long DNA sequence data are made into a prototype of fragment of about 700 bases that can be analyzed by automatic sequence analyzer at one time, and then matching ratio is calculated by comparing a standard prototype with 3 fragmented clones of about 700 bases generated by the PCR method. In this process, the time for calculation of matching ratio is reduced by Compute Agreement algorithm. Two candidates of combined fragments of every prototype are extracted by the degree of overlapping of calculated fragment pairs, and then degree of combination is decided using a fuzzy reasoning method that utilizes the matching ratios of each extracted fragment, and A, C, G, T membership degrees of each DNA sequence, and previous frequencies of each A, C, G, T. In this paper. DNA sequence combination is completed by the iteration of the process to combine decided optimal test fragments until no fragment remains. For the experiments, fragments or about 700 bases were generated from each sequence of 10,000 bases and 100,000 bases extracted from 'PCC6803', complete protein genome. From the experiments by applying random notations on these fragments, we could see that the proposed method was faster than FAP program, and combination failure, defect of conventional contig assembly programs, did not occur.