• Title/Summary/Keyword: accelerating convergence

검색결과 123건 처리시간 0.212초

AN ACCELERATING SCHEME OF CONVERGENCE TO SOLVE FUZZY NON-LINEAR EQUATIONS

  • Jun, Younbae
    • 한국수학교육학회지시리즈B:순수및응용수학
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    • 제24권1호
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    • pp.45-51
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    • 2017
  • In this paper, we propose an accelerating scheme of convergence of numerical solutions of fuzzy non-linear equations. Numerical experiments show that the new method has significant acceleration of convergence of solutions of fuzzy non-linear equation. Three-dimensional graphical representation of fuzzy solutions is also provided as a reference of visual convergence of the solution sequence.

Derivative Evaluation and Conditional Random Selection for Accelerating Genetic Algorithms

  • Jung, Sung-Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제5권1호
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    • pp.21-28
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    • 2005
  • This paper proposes a new method for accelerating the search speed of genetic algorithms by taking derivative evaluation and conditional random selection into account in their evolution process. Derivative evaluation makes genetic algorithms focus on the individuals whose fitness is rapidly increased. This accelerates the search speed of genetic algorithms by enhancing exploitation like steepest descent methods but also increases the possibility of a premature convergence that means most individuals after a few generations approach to local optima. On the other hand, derivative evaluation under a premature convergence helps genetic algorithms escape the local optima by enhancing exploration. If GAs fall into a premature convergence, random selection is used in order to help escaping local optimum, but its effects are not large. We experimented our method with one combinatorial problem and five complex function optimization problems. Experimental results showed that our method was superior to the simple genetic algorithm especially when the search space is large.

ON THE GENERALIZED SOR-LIKE METHODS FOR SADDLE POINT PROBLEMS

  • Feng, Xin-Long;Shao, Long
    • Journal of applied mathematics & informatics
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    • 제28권3_4호
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    • pp.663-677
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    • 2010
  • In this paper, the generalized SOR-like methods are presented for solving the saddle point problems. Based on the SOR-like methods, we introduce the uncertain parameters and the preconditioned matrixes in the splitting form of the coefficient matrix. The necessary and sufficient conditions for guaranteeing its convergence are derived by giving the restrictions imposed on the parameters. Finally, numerical experiments show that this methods are more effective by choosing the proper values of parameters.

사회적 관점에 의한 슬로 패션의 특성과 미적 가치 (The Characteristics and Aesthetic Values of Slow Fashion from a Social Viewpoint)

  • 노주현;김민자
    • 한국의류학회지
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    • 제35권11호
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    • pp.1386-1398
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    • 2011
  • Slow fashion can be viewed as an activism that provides an alternative solution to the problematic issues of fast fashion in a practical sense; however, (from a theoretical point of view) it is a fashion phenomenon arising from the criticism of an accelerating society. Slowness emphasizes the virtues of moderation. Slowness refers to the recovery of human ethics that have been neglected due to the goal-oriented nature of an accelerating society. Slowness can solve the problem of conformity and discrimination in society through pluralism and respect for local indigenousness. The characteristics of slow fashion can be defined by the aesthetic values of circularity, sustainability, moderation, expressivity and convergence. This includes the beauty of circularity (which views the relationships of all processes as organic), the beauty of sustainability (which ensures the maintenance of continuous emotions and the durability of products that can be promoted through slow processes), the beauty of moderation (which places importance on spiritual values and the moderate use of materials), and the beauty of expressivity (which plays the role of a social messenger that facilitates social assertion). These combined values present the beauty of convergence such as the harmony of local communities and the world in a blend of the old and the new with an exchange between producers and consumers.

무인차량 원격주행제어 신뢰성 향상을 위한 통합 시뮬레이터 구축에 관한 연구 (A Study on the Development of Driving Simulator for Improvement of Unmanned Vehicle Remote Control)

  • 강태완;박기홍;김준원;김재관;박현철;강창근
    • 한국산학기술학회논문지
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    • 제20권6호
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    • pp.86-94
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    • 2019
  • 본 논문은 보다 높은 실재감과 안전성을 확보하기 위한 무인차량 원격주행제어 환경 개발에 대한 내용을 설명한다. 주로 무인차량 원격주행제어를 위한 환경은 조이스틱 형태의 장치를 활용하여 조향과 가/감속이 가능하도록 개발되어 사용되었다. 그 외 일반 차량처럼 간이 조향-휠(steering-wheel)을 기반으로 개발된 시뮬레이터 환경도 있으나, 현재 주행 상황을 피드백하는 기술이 적용되어 있지 않거나 가/감속부를 포함하지 않는 것이 대부분이다. 피드백 기술이란 일반 차량을 직접 운전할 때 조향-휠과 가/감속 페달을 통해 느껴지는 현재 주행 상황을 시뮬레이터 환경에 구현하는 것을 의미한다. 이렇듯 무인차량 원격주행제어에 이질감을 감소시키는 피드백 기술 개발과 더불어 실재감을 높일 수 있는 시뮬레이터 환경 구축이 필수적이다. 따라서 본 연구에서는 선행 연구를 통해 개발된 힘반향 햅틱제어 기술을 적용할 수 있는 시뮬레이터 환경을 구축하고 시뮬레이터 하드웨어의 최소 요구사양을 도출하는 연구를 수행하였다. 하드웨어 구성은 일반 차량과 유사한 조향-휠 모듈과 가/감속 페달 모듈로 구성하였으며, 조향부와 가/감속부 모두 피드백 기술을 적용할 수 있도록 별도의 액추에이터를 설치하였다. 또한 제어부 PC를 통해 두 가지 조작부에 피드백 명령을 전달할 수 있도록 CAN(controller area network) 통신 환경을 구성하였다. 이렇게 구성한 시뮬레이터 환경의 성능을 검증하기 위하여 기 개발된 힘반향 햅틱제어 알고리즘을 직접 적용하여 각 상황 별 알고리즘 동작을 평가하였다.

IoT-based Digital Life Care Industry Trends

  • Kim, Young-Hak
    • International journal of advanced smart convergence
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    • 제8권3호
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    • pp.87-94
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    • 2019
  • IoT-based services are being released in accordance with the aging population and the demand for well-being pursuit needs. In addition to medical device companies, companies with ideas ranging from global ICT companies to startup companies are accelerating their market entry. The areas where these services are most commonly applied are health/medical, life/safety, city/energy, automotive and transportation. Furthermore, by expanding IoT technology convergence into the area of life care services, it contributes greatly to the development of service models in the public sector. It also provides an important opportunity for IoT-related companies to open up new markets. By addressing the problems of life care services that are still insufficient. We are providing opportunities to pursue the common interests of both users and workers and improve the quality of life. In order to establish IoT-based digital life care services, it is necessary to develop convergence technologies using cloud computing systems, big data analytics, medical information, and smart healthcare infrastructure.

A PROJECTION ALGORITHM FOR SYMMETRIC EIGENVALUE PROBLEMS

  • PARK, PIL SEONG
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제3권2호
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    • pp.5-16
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    • 1999
  • We introduce a new projector for accelerating convergence of a symmetric eigenvalue problem Ax = x, and devise a power/Lanczos hybrid algorithm. Acceleration can be achieved by removing the hard-to-annihilate nonsolution eigencomponents corresponding to the widespread eigenvalues with modulus close to 1, by estimating them accurately using the Lanczos method. However, the additional Lanczos results can be obtained without expensive matrix-vector multiplications but a very small amount of extra work, by utilizing simple power-Lanczos interconversion algorithms suggested. Numerical experiments are given at the end.

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Competitive Generation for Genetic Algorithms

  • Jung, Sung-Hoon
    • 한국지능시스템학회논문지
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    • 제17권1호
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    • pp.86-93
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    • 2007
  • A new operation termed competitive generation in the processes of genetic algorithms is proposed for accelerating the optimization speed of genetic algorithms. The competitive generation devised by considering the competition of sperms for fertilization provides a good opportunity for the genetic algorithms to approach global optimum without falling into local optimum. Experimental results with typical problems showed that the genetic algorithms with competitive generation are superior to those without the competitive generation.

합성곱 신경망의 학습 가속화를 위한 방법 (A Method for accelerating training of Convolutional Neural Network)

  • 최세진;정준모
    • 문화기술의 융합
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    • 제3권4호
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    • pp.171-175
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    • 2017
  • 최근 CNN(Convolutional Neural Network)의 구조가 복잡해지고 신견망의 깊이가 깊어지고 있다. 이에 따라 신경망의 학습에 요구되는 연산량 및 학습 시간이 증가하게 되었다. 최근 GPGPU 및 FPGA를 이용하여 신경망의 학습 속도를 가속화 하는 방법에 대한 연구가 활발히 진행되고 있다. 본 논문에서는 NVIDIA GPGPU를 제어하는 CUDA를 이용하여 CNN의 특징추출부와 분류부에 대한 연산을 가속화하는 방법을 제시한다. 특징추출부와 분류부에 대한 연산을 GPGPU의 블록 및 스레드로 할당하여 병렬로 처리하였다. 본 논문에서 제안하는 방법과 기존 CPU를 이용하여 CNN을 학습하여 학습 속도를 비교하였다. MNIST 데이터세트에 대하여 총 5 epoch을 학습한 결과 제안하는 방법이 CPU를 이용하여 학습한 방법에 비하여 약 314% 정도 학습 속도가 향상된 것을 확인하였다.