• Title/Summary/Keyword: Hierarchical optimization

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GA based Fuzzy Modeling using Fuzzy Equalization and Linguistic Hedge (퍼지 균등화와 언어적인 Hedge를 이용한 GA 기반 퍼지 모델링)

  • 김승석;곽근창;유정웅;전명근
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.12a
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    • pp.217-220
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    • 2001
  • The fuzzy equalization method does not require the usual learning step for generating fuzzy rules. However it is heavily depend on the given input-output data set. So, we adapt an hierarchical scheme which sequentially optimizes the fuzzy inference system. Here, the parameters of fuzzy membership functions obtained from the fuzzy equalization are optimized by the genetic algorithm, and then they are also modified to increase the performance index using the linguistic hedge. Finally, we applied it to the Rice taste data and got better results than previous ones.

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Optimization of Biomimetic Two-level Hierarchical Adhesive System (자연모사 2층 구조 응착시스템의 최적화)

  • Kim, Tae-Wan
    • Tribology and Lubricants
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    • v.26 no.2
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    • pp.129-135
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    • 2010
  • Geckos have a unique ability to cling to ceilings and walls utilizing dry adhesion. Their foot pads are covered by a large number of small hairs (setae) that contain many branches per seta with a lower level of spatulae. Their fibrillar structure is the primary source of high adhesion. In this study, we construct the adhesion design database for biomimetic adhesive system. A simple idealized fibrillar structure consisting of single array of beams is modeled. The fibers are assumed as oriented cylindrical cantilever beams with spherical tip. We consider three necessary conditions; buckling, fracture and sticking of fiber structure, which constrain the allowed geometry. The adhesion analysis is performed for the attachment system in contact with rough surfaces with different s values for different main design variables-fiber radius, aspect ratio and material elastic modulus and so on. The developed adhesion design databases are useful for understanding biological systems and for guiding of fabrication of the biomimetic attachment system.

A Two-Stage Method for Near-Optimal Clustering (최적에 가까운 군집화를 위한 이단계 방법)

  • 윤복식
    • Journal of the Korean Operations Research and Management Science Society
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    • v.29 no.1
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    • pp.43-56
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    • 2004
  • The purpose of clustering is to partition a set of objects into several clusters based on some appropriate similarity measure. In most cases, clustering is considered without any prior information on the number of clusters or the structure of the given data, which makes clustering is one example of very complicated combinatorial optimization problems. In this paper we propose a general-purpose clustering method that can determine the proper number of clusters as well as efficiently carry out clustering analysis for various types of data. The method is composed of two stages. In the first stage, two different hierarchical clustering methods are used to get a reasonably good clustering result, which is improved In the second stage by ASA(accelerated simulated annealing) algorithm equipped with specially designed perturbation schemes. Extensive experimental results are given to demonstrate the apparent usefulness of our ASA clustering method.

Optimization of IG_based Fuzzy Set Fuzzy Model by Means of Adaptive Hierarchical Fair Competition-based Genetic Algorithms (적응형 계층적 공정 경쟁 유전자 알고리즘을 이용한 정보입자 기반 퍼지집합 퍼지모델의 최적화)

  • Choe, Jeong-Nae;O, Seong-Gwon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2006.11a
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    • pp.366-369
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    • 2006
  • 본 논문에서는 계층적 공정 경쟁 유전자 알고리즘을 통한 비선형시스템의 정보입자 기반 퍼지집합 퍼지집합 모델의 최적화 방법을 제안한다. 퍼지집합 모델은 주로 전문가의 경험에 기반을 두어 얻어지기 때문에 동정과 최적화 과정이 필요하며 GAs를 이용하여 퍼지모델을 최적화한 연구가 많이 있다. GAs는 전역 해를 찾을 수 있는 최적화 알고리즘으로 잘 알려져 있지만 조기 수렴 문제를 포함하고 있다. 병렬유전자 알고리즘(PGA)은 조기수렴를 더디게 하고 전역 해를 찾기 위한 진화알고리즘이다. 적응형 계층적 공정 경쟁기반 유전자 알고리즘(AHFCGA)을 이용하여 퍼지모델의 입력변수, 멤버쉽함수의 수, 멤버쉽함수의 정점 등의 전반부 구조와 파라미터를 동정하였고, LSE를 사용하여 후반부 파라미터를 동정하였으며 실험적 예제를 통하여 제안된 방법의 성능을 평가한다.

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Hierarchical Risk Parity Portfolio Optimization via Nonlinear Measures Considering Finite Size Effects (유한 크기 효과를 고려한 비선형 의존성 지표를 활용한 계층적 리스크 패리티 모형 기반 포트폴리오 최적화 )

  • Insu Choi;Woo Chang Kim
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.8-10
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    • 2023
  • 본 연구는 계층적 리스크 패리티 (Hierarchical Risk Parity, HRP) 포트폴리오 방법론과 정규화된 상호 정보 거리의 결합을 연구하였다. 이때, 한정된 이동창에서 발생할 수 있는 유한 크기 효과(finite size effects) 문제를 극복하기 위해 무작위로 섞인 NID 값에 대한 평균치를 제공함에 따라 NID 를 활용한 새로운 포트폴리오 최적화 방법을 제안한다. 본 연구의 결과는 NID 를 통합한 HRP 포트폴리오가 기존 방법론에 비해 통계적 장점과 함께 더욱 효율적이며 안정적임을 보여준다.

Integer Programming Approach to Line Optimization of Multiple Surface Mounters (정수계획법에 의한 다수 표면실장기의 라인 최적화)

  • Kim Kyung-Min;Park Tae-Hyoung
    • The Journal of the Korea Contents Association
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    • v.6 no.4
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    • pp.46-54
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    • 2006
  • We propose an optimization method for PCB assembly lines including multiple surface mounters. To increase the productivity of PCB assembly line, the component allocation, feeder assignment, and assembly sequence of each surface mounter should be optimized. The optimization Problem is formulated as an integer programming problem. We divide the overall problem into two hierarchical sub-problems: forward-path problem and backward-path problem. The clustering algorithm and branch-and-bound algorithm are applied to solve the forward-path problem. The assignment algorithm and connection algorithm are applied to solve the backward-path problem. Simulation results are presented to verify the usefulness of the proposed method.

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A Hierarchical Packet Classification Algorithm Using Set-Pruning Binary Search Tree (셋-프루닝 이진 검색 트리를 이용한 계층적 패킷 분류 알고리즘)

  • Lee, Soo-Hyun;Lim, Hye-Sook
    • Journal of KIISE:Information Networking
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    • v.35 no.6
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    • pp.482-496
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    • 2008
  • Packet classification in the Internet routers requires multi-dimensional search for multiple header fields for every incoming packet in wire-speed, hence packet classification is one of the most important challenges in router design. Hierarchical packet classification is one of the most effective solutions since search space is remarkably reduced every time a field search is completed. However, hierarchical structures have two intrinsic issues; back-tracking and empty internal nodes. In this paper, we propose a new hierarchical packet classification algorithm which solves both problems. The back-tracking is avoided by using the set-pruning and the empty internal nodes are avoided by applying the binary search tree. Simulation result shows that the proposed algorithm provides significant improvement in search speed without increasing the amount of memory requirement. We also propose an optimization technique applying controlled rule copy in set-pruning.

Loss-Aware Rate-Distortion Optimization for Redundant Picture in H.264/AVC (H.264/AVC를 위한 에러 적응형 예비 슬라이스)

  • Lee, Jin-Ho;Choi, Jin-Soo;Choi, Hae-Chul
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2008.11a
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    • pp.85-88
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    • 2008
  • 예비 슬라이스(Redundant picture)는 에러가 발생하기 쉬운 환경에서 비디오가 전송될 때 에러를 보상하기 위한 H.264/AVC 부호화 표준의 도구들 중에 하나이다. 본 논문에서는 예비 슬라이스의 삽입으로 인해 발생하는 오버헤드 비트와 손실률을 고려한 LA-RDO(Loss-aware rate-distortion optimization) 모델을 제시하며 제안하는 모델에 기초해서 예비 슬라이스의 삽입 여부를 결정한다. 실험결과는 제안하는 방법이 참조 소프트웨어(JM: Joint Model)에 있는 HRP(Hierarchical redundant picture)와 비교했을 때 평균 0.5dB의 PSNR이 증가함을 보였다. 특별히 낮은 비트율에서 상대적으로 높은 성능을 보이므로 비디오 화상 회의와 같이 낮은 비트의 영상을 요구하는 무선 전송 환경에 적합할 것으로 보인다.

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Solving Mixed Strategy Equilibria of Multi-Player Games with a Transmission Congestion (다자게임 전력시장에서 송전선 혼잡시의 복합전략 내쉬균형 계산)

  • Lee, Kwang-Ho
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.55 no.11
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    • pp.492-497
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    • 2006
  • Nash Equilibrium (NE) is essential to investigate a participant's bidding strategy in a competitive electricity market. The transmission line constraints make it difficult to compute the NE due to causing a mixed strategy NE instead of a pure strategy NE. Computing a mixed strategy is more complicated in a multi-player game. The competition among multi-participants is modeled by a two-level hierarchical optimization problem. A mathematical programming approach is widely used in finding this equilibrium. However, there are difficulties to solving a mixed strategy NE. This paper presents two propositions to add heuristics to the mathematical programming method. The propositions are based on empirical studies on mixed strategies in numerous sample systems. Based on the propositions a new formulation is provided with a set of linear and nonlinear equations, and an algorithm is suggested for using the prepositions and the newly-formulated equations.

Optimization of preventive maintenance of nuclear safety-class DCS based on reliability modeling

  • Peng, Hao;Wang, Yuanbing;Zhang, Xu;Hu, Qingren;Xu, Biao
    • Nuclear Engineering and Technology
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    • v.54 no.10
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    • pp.3595-3603
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    • 2022
  • Nuclear safety-class DCS is used for nuclear reactor protection function, which is one of the key facilities to ensure nuclear power plant safety, the maintenance for DCS to keep system in a high reliability is significant. In this paper, Nuclear safety-class DCS system developed by the Nuclear Power Institute of China is investigated, the model of reliability estimation considering nuclear power plant emergency trip control process is carried out using Markov transfer process. According to the System-Subgroup-Module hierarchical iteration calculation, the evolution curve of failure probability is established, and the preventive maintenance optimization strategy is constructed combining reliability numerical calculation and periodic overhaul interval of nuclear power plant, which could provide a quantitative basis for the maintenance decision of DCS system.