• 제목/요약/키워드: K-means++ algorithm

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물체인식을 위한 영상분할 기법과 퍼지 알고리듬을 이용한 유사도 측정 (An Image Segmentation Method and Similarity Measurement Using fuzzy Algorithm for Object Recognition)

  • 김동기;이성규;이문욱;강이석
    • 대한기계학회논문집A
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    • 제28권2호
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    • pp.125-132
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    • 2004
  • In this paper, we propose a new two-stage segmentation method for the effective object recognition which uses region-growing algorithm and k-means clustering method. At first, an image is segmented into many small regions via region growing algorithm. And then the segmented small regions are merged in several regions so that the regions of an object may be included in the same region using typical k-means clustering method. This paper also establishes similarity measurement which is useful for object recognition in an image. Similarity is measured by fuzzy system whose input variables are compactness, magnitude of biasness and orientation of biasness of the object image, which are geometrical features of the object. To verify the effectiveness of the proposed two-stage segmentation method and similarity measurement, experiments for object recognition were made and the results show that they are applicable to object recognition under normal circumstance as well as under abnormal circumstance of being.

차감 및 중력 fuzzy C-means 클러스터링을 이용한 칼라 영상 분할에 관한 연구 (Segmentation of Color Image by Subtractive and Gravity Fuzzy C-means Clustering)

  • 진영근;김태균
    • 전기전자학회논문지
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    • 제1권1호
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    • pp.93-100
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    • 1997
  • 칼라 영상 분할의 한 방법으로 fuzzy C-means를 이용한 방법이 많이 연구되었으나, 이 방법은 클러스터의 개수가 정해져야 사용할 수 있는 방법이다. 분할해야 할 데이터가 많은 경우 예비 분할을 수행하여 예비 분할 되지 않는 데이터들에 대해서 상세 분할을 fuzzy C-means를 사용하여 분할 하나 예비 분할된 데이터의 클러스터 중심과 상세 분할로 만들어진 클러스터의 중심과는 연계성이 없어진다. 본 연구에서는 이것을 보완하기 위하여 차감 클러스터링을 사용하여 칼라 영상의 클러스터의 개수와 중심을 구한 후, 이것을 이용하여 영상을 예비 분할하고 중력을 가진 fuzzy C-means를 사용하여 분할되지 않은 나머지 부분과 클러스터의 중심을 최적화 시켜 분할하는 알고리듬을 제안한다. 제안된 방법의 정성적인 평가를 수행하여 본 논문에서 제시된 방법이 우수함을 보인다.

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EEC-FM: Energy Efficient Clustering based on Firefly and Midpoint Algorithms in Wireless Sensor Network

  • Daniel, Ravuri;Rao, Kuda Nageswara
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권8호
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    • pp.3683-3703
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    • 2018
  • Wireless sensor networks (WSNs) consist of set of sensor nodes. These sensor nodes are deployed in unattended area which are able to sense, process and transmit data to the base station (BS). One of the primary issues of WSN is energy efficiency. In many existing clustering approaches, initial centroids of cluster heads (CHs) are chosen randomly and they form unbalanced clusters, results more energy consumption. In this paper, an energy efficient clustering protocol to prevent unbalanced clusters based on firefly and midpoint algorithms called EEC-FM has been proposed, where midpoint algorithm is used for initial centroid of CHs selection and firefly is used for cluster formation. Using residual energy and Euclidean distance as the parameters for appropriate cluster formation of the proposed approach produces balanced clusters to eventually balance the load of CHs and improve the network lifetime. Simulation result shows that the proposed method outperforms LEACH-B, BPK-means, Park's approach, Mk-means, and EECPK-means with respect to balancing of clusters, energy efficiency and network lifetime parameters. Simulation result also demonstrate that the proposed approach, EEC-FM protocol is 45% better than LEACH-B, 17.8% better than BPK-means protocol, 12.5% better than Park's approach, 9.1% better than Mk-means, and 5.8% better than EECPK-means protocol with respect to the parameter half energy consumption (HEC).

Training HMM Structure and Parameters with Genetic Algorithm and Harmony Search Algorithm

  • Ko, Kwang-Eun;Park, Seung-Min;Park, Jun-Heong;Sim, Kwee-Bo
    • Journal of Electrical Engineering and Technology
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    • 제7권1호
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    • pp.109-114
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    • 2012
  • In this paper, we utilize training strategy of hidden Markov model (HMM) to use in versatile issues such as classification of time-series sequential data such as electric transient disturbance problem in power system. For this, an automatic means of optimizing HMMs would be highly desirable, but it raises important issues: model interpretation and complexity control. With this in mind, we explore the possibility of using genetic algorithm (GA) and harmony search (HS) algorithm for optimizing the HMM. GA is flexible to allow incorporating other methods, such as Baum-Welch, within their cycle. Furthermore, operators that alter the structure of HMMs can be designed to simple structures. HS algorithm with parameter-setting free technique is proper for optimizing the parameters of HMM. HS algorithm is flexible so as to allow the elimination of requiring tedious parameter assigning efforts. In this paper, a sequential data analysis simulation is illustrated, and the optimized-HMMs are evaluated. The optimized HMM was capable of classifying a sequential data set for testing compared with the normal HMM.

An improved algorithm for the exchange heuristic for solving multi-project multi-resource constrained scheduling with variable-intensity activities

  • Yu, Jai-Keon;Kim, Won-Kyung
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 1993년도 춘계공동학술대회 발표논문 및 초록집; 계명대학교, 대구; 30 Apr.-1 May 1993
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    • pp.343-352
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    • 1993
  • In this study, a modified algorithm for the exchange heuristic is developed and applied to a resource-constrained scheduling problem. The problem involves multiple projects and multiple resource categories and allows flexible resource allocation to each activity. The objective is to minimize the maximum completion time. The exchange heuristkc is a multiple pass algorithm which makes improvements upon a given initial feasible schedule. Four different modified algorithms are proposed. The original algorithm and the new algorithms were compared through an experimental investigation. All the proposed algorithms reduce the maximum completion time much more effectively than the original algorithm. Especially, one of four proposed algorithms obviously outperforms the other three algorithms. The algorithm of the best performance produces significantly shorter schedules than the original algorithm, though it requires up to three times more computation time. However, in most situations, a reduction in schedule length means a significant reduction in the total cost.

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Clarifying Warhead Separation from the Reentry Vehicle Using a Novel Tracking Algorithm

  • Liu Cheng-Yu;Sung Yu-Ming
    • International Journal of Control, Automation, and Systems
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    • 제4권5호
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    • pp.529-538
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    • 2006
  • Separating a reentry vehicle into warhead and body is a conventional and efficient means of producing a huge decoy and increasing the kinetic energy of the warhead. This procedure causes the radar to track the body, whose radar cross section is larger, and ignore the warhead, which is the most important part of the reentry vehicle. However, the procedure is difficult to perform using standard tracking criteria. This study presents a novel tracking algorithm by integrating input estimation and modified probabilistic data association filter to solve this difficulty in a clear environment. The proposed algorithm with a new defined association probability in this filter provides a good tracking capability for the warhead ignoring the radar cross section. The simulation results indicate that the errors between the estimated and the warhead trajectories are reduced to a small interval in a short time. Therefore, the radar can produce a beam to illuminate to the right area and keep tracking the warhead all the way. In conclusion, this algorithm is worthy of further study and application.

환상형 분산전원 단지 보호를 위한 전압제어 과전류 계전기 (Voltage-controlled Over-current Relay for Loop-connected Distributed Generators)

  • 김태희;강상희
    • 전기학회논문지
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    • 제65권12호
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    • pp.1979-1985
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    • 2016
  • A protection algorithm using a voltage-controlled overcurrent element for a looped collection circuit in a wind farm is suggested in this paper. Because the proposed algorithm uses voltage relaying signals as well as current relaying signals, any fault in the looped collection circuit can be cleared by voltage-controlled overcurrent relays located at the two adjacent relaying points, the nearest place in each direction from the fault point. The algorithm can also distinguish the external faults which occur at the outside of a wind farm from the internal faults. It means that the proposed algorithm can provide the proper ability of protection coordination to the relays in the looped collection circuits of a large wind farm. The performance of the proposed algorithm is verified under various fault conditions using PSCAD/EMTDC simulations.

유전자 알고리즘을 이용한 퍼지 제어규칙의 최적동조 (Optimal Auto-tuning of Fuzzy control rules by means of Genetic Algorithm)

  • 김중영;이대근;오성권;장성환
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
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    • pp.588-590
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    • 1999
  • In this paper the design method of a fuzzy logic controller with a genetic algorithm is proposed. Fuzzy logic controller is based on linguistic descriptions(in the form of fuzzy IF-THEN rules) from human experts. The auto-tuning method is presented to automatically improve the output performance of controller utilizing the genetic algorithm. The GA algorithm estimates automatically the optimal values of scaling factors and membership function parameters of fuzzy control rules. Controllers are applied to the processes with time-delay and the DC servo motor. Computer simulations are conducted at the step input and the output performances are evaluated in the ITAE.

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대칭분 전류를 이용한 송전선로 보호용 고장상 선택 알고리즘 (Phase Selection Algorithm Symmetrical Components for Transmission Line Protection)

  • 이승재;이명수;이재규;유석구
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 A
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    • pp.22-24
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    • 2001
  • This paper presents a fault phase selection algorithm for transmission line protection by means of the symmetrical components. Accurate fault phase selection is necessary for collect functioning of transmission line relaying, particularly in Extra High Voltage (EHV) networks. The conventional phase selection algorithm used the phase difference between positive and negative sequence current excluding load current. But, it is difficult to abstract only fault current since we can not know the time which a fault occurs. The proposed algorithm can select the accurately fault phase using fault current contained pre-fault current.

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Augmenting Quasi-Tree Search Algorithm for Maximum Homogenous Information Flow with Single Source/Multiple Sinks

  • Fujita, Koichi;Watanabe, Hitoshi
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -1
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    • pp.462-465
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    • 2002
  • This paper presents a basic theory of information flow from single sending point to multiple receiving points, where new theories of algebraic system called "Hybrid Vector Space" and flow vector space play important roles. Based on the theory, a new algorithm for finding maximum homogenous information flow is proposed, where homogenous information flow means the flow of the same contents of information delivered to multiple clients at a time. Effective multi-routing algorithms fur tree-shape delivery rout search are presented.

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