• 제목/요약/키워드: Algorithms

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Enhanced Machine Learning Algorithms: Deep Learning, Reinforcement Learning, and Q-Learning

  • Park, Ji Su;Park, Jong Hyuk
    • Journal of Information Processing Systems
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    • 제16권5호
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    • pp.1001-1007
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    • 2020
  • In recent years, machine learning algorithms are continuously being used and expanded in various fields, such as facial recognition, signal processing, personal authentication, and stock prediction. In particular, various algorithms, such as deep learning, reinforcement learning, and Q-learning, are continuously being improved. Among these algorithms, the expansion of deep learning is rapidly changing. Nevertheless, machine learning algorithms have not yet been applied in several fields, such as personal authentication technology. This technology is an essential tool in the digital information era, walking recognition technology as promising biometrics, and technology for solving state-space problems. Therefore, algorithm technologies of deep learning, reinforcement learning, and Q-learning, which are typical machine learning algorithms in various fields, such as agricultural technology, personal authentication, wireless network, game, biometric recognition, and image recognition, are being improved and expanded in this paper.

Fast Optimization by Queen-bee Evolution and Derivative Evaluation in Genetic Algorithms

  • Jung, Sung-Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제5권4호
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    • pp.310-315
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    • 2005
  • This paper proposes a fast optimization method by combining queen-bee evolution and derivative evaluation in genetic algorithms. These two operations make it possible for genetic algorithms to focus on highly fitted individuals and rapidly evolved individuals, respectively. Even though the two operations can also increase the probability that genetic algorithms fall into premature convergence phenomenon, that can be controlled by strong mutation rates. That is, the two operations and the strong mutation strengthen exploitation and exploration of the genetic algorithms, respectively. As a result, the genetic algorithm employing queen-bee evolution and derivative evaluation finds optimum solutions more quickly than those employing one of them. This was proved by experiments with one pattern matching problem and two function optimization problems.

분산시스템에서 부하공유 알고리즘의 천이특성 해석 (Analysis of transient Characteristics of Load Sharing Algorithms In Distributed Systems)

  • 박세명
    • 한국시뮬레이션학회논문지
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    • 제2권1호
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    • pp.91-106
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    • 1993
  • Load sharing in distributed systems improves systems performance. Research in the field has been focused on steady state performance for load sharing algorithms. However, transient characteristics of such algorithms may be important in a distributed system in which workload for some node is changing. Simulation is the only means to analyze such characteristics. This paper presents a simulation-based analysis of the transient characteristics of four load sharing algorithms ; forward probing, reverse probing, symmetric probing, and multi-threshold symmetric probing algorithms. Discrete event system models for execution of the algorithms in a distributed system has been developed in a SIMSCRIOT II.5 environment. Simulation results indicate that the MSYM algorithm shows the shortest response time in the transient period.

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Evolutionary Algorithms for Finding the k Most Vital Arcs in Minimum Spanning Tree Problem

  • Ho Yeon Chung
    • 산업경영시스템학회지
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    • 제24권68호
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    • pp.21-30
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    • 2001
  • The purpose of this study is to present methods for determining the k most vital arcs (k-MVAs) in the minimum spanning tree problem(MSTP) using evolutionary algorithms. The problem of finding the k-MVAs in MSTP is to find a set of k arcs whose simultaneous removal from the network causes the greatest increase in the total length of minimum spanning tree. Generally, the problem which determine the k-MVAs in MSTP has known as NP-hard. Therefore, in order to deal with the problem of real world the heuristic algorithms are needed. In this study we propose to three genetic algorithms as the heuristic methods for finding the k-MVAs in MSTP. The algorithms to be presented in this study are developed using the library of the evolutionary algorithm framework(EAF) and the performance of the algorithms are analyzed through the computer experiment.

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On Performance Analysis of Position Based Routing Algorithms in Wireless Networks

  • 단 디 쉬엔;공형윤
    • 한국통신학회논문지
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    • 제35권6A호
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    • pp.538-546
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    • 2010
  • This paper presents an overview of position-based routing algorithms. We analyze performances of routing algorithms such as Hybrid Opportunistic Forwarding (HOF), Opportunistic multi-hop routing (ExOR), Location based Geocasting and Forwarding (LGF), and Greedy Forwarding in nearest with forward Progress (GFP) routing algorithms to find the best one in terms of packet error rate and throughput efficiency over effects of fading and noise variance in wireless networks. The analyses in closed form expressions are confirmed by the simulation results, which fully agree to analysis results. Additionally, the simulation results indicate significant differences among algorithms when varying the average SNR or the number of relays.

Low-Complexity Network Coding Algorithms for Energy Efficient Information Exchange

  • Wang, Yu;Henning, Ian D.
    • Journal of Communications and Networks
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    • 제10권4호
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    • pp.396-402
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    • 2008
  • The use of network coding in wireless networks has been proposed in the literature for energy efficient broadcast. However, the decoding complexity of existing algorithms is too high for low-complexity devices. In this work we formalize the all-to-all information exchange problem and shows how to optimize the transmission scheme in terms of energy efficiency. Furthermore, we prove by construction that there exists O(1) -complexity network coding algorithms for grid networks which can achieve such optimality. We also present low-complexity heuristics for random. topology networks. Simulation results show that network coding algorithms outperforms forwarding algorithms in most cases.

분산시스템에서 가상 체크포인팅을 이용한 비동기화 체크포인팅 알고리즘 (An Asychronous Checkpointing Algorithm Using Virtual Checkpointing On Distributed Systems)

  • 김도형;박창순;김종
    • 한국정보처리학회논문지
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    • 제6권5호
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    • pp.1203-1211
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    • 1999
  • Checkpointing is the one of fault-tolerant techniques to restore faults and to restart job fast. Checkpointing algorithms in distributed systems have been studied for many years. These algorithms can be classified into synchronous Checkpointing algorithms and asynchronous Checkpoiting algorithms. In this paper, we propose an independent Checkpointing algorithm that has a minimum Checkpointing counts equal to periodic Checkpointing algorithm, and relatively short rollback distance at faulty situation. Checkpointing count is directly related to task completion time in a fault-free situation and short rollback distance is directly related to task completion time in a faulty situation. The proposed algorithm is compared with the previously proposed asynchronous Checkpointing algorithms using simulation. In the simulation, the proposed Checkpointing algorithm produces better results than other algorithms in terms of task completion time in fault-free as well as faulty situations.

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블라인드 워터마킹: 튜토리얼 (Blind Watermarking Algorithms: A Tutorial)

  • 김형중;여인권
    • 방송공학회논문지
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    • 제6권3호
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    • pp.270-282
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    • 2001
  • 이 논문은 현재 잘 알려진 3종류의 블라인드 워터마크 삽입 및 검출방법을 신호처리 관점에서 소개한다. 이들 3가지는 각각 상 관관계기반 방법, 에코기반 방법, 그리고 패치워크 방법이다. 이들 방법은 시간영역 (또는 공간영역) 또는 변환영역에서 적용할 수 있다. 이 논문에서는 이들 세 방법을 구현하는데 필요한 기초이론 및 구현방법을 제공한다. 아울러 실제 약간의 실험 결과들을 포함시켰다.

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고성능 분산 합의 알고리즘 동향 분석 (Trend Analysis of High-Performance Distributed Consensus Algorithms)

  • 진희상;김동오;김영창;오진태;김기영
    • 전자통신동향분석
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    • 제37권1호
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    • pp.63-72
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    • 2022
  • Recently, blockchain has been attracting attention as a high-reliability technology in various fields. However, the Proof-of-Work-based distributed consensus algorithm applied to representative blockchains, such as Bitcoin and Ethereum, has limitations in applications to various industries owing to its excessive resource consumption and performance limitations. To overcome these limitations, various distributed consensus algorithms have appeared, and recently, hybrid distributed consensus algorithms that use two or more consensus algorithms to achieve decentralization and scalability have emerged. This paper introduces the technological trends of the latest high-performance distributed consensus algorithms by analyzing representative hybrid distributed consensus algorithms.

ALGORITHMS FOR COMPUTING OF HILBERT FUNCTIONS

  • Shin, Dong-Soo
    • Journal of applied mathematics & informatics
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    • 제12권1_2호
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    • pp.375-384
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    • 2003
  • We introduce some algorithms for computing Mathematics and also give some questions based on the results from computations using CoCoA and Splus.