• 제목/요약/키워드: Search techniques

검색결과 969건 처리시간 0.034초

Hybrid Genetic Algorithms with Conditional Local Search

  • Yun, Young-Su;Seo, Seung-Lock;Kim, Jong-Hwan;Chiung Moon
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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    • pp.183-186
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    • 2003
  • Hybrid genetic algorithms (HGAs) have been studied as various ways. These HGAs usually use both the global search property of genetic algorithm (GA) and the local search one of local search techniques. One of the general types, when constructing HGAs, is to incorporate a local search technique into GA loop, and then the local search technique is repeated as many iteration number as the loop. This paper proposes a new HGA with a conditional local search technique (c-HGA) that does not be repeated as many iteration number as GA loop. For effectiveness of the proposed c-HGA, a conventional HGA and GA are also suggested, and then these algorithms are compared with each other in numerical examples,

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시공간 상관성을 이용한 적응적 움직임 추정 (Adaptive motion estimation based on spatio-temporal correlations)

  • 김동욱;김진태;최종수
    • 한국통신학회논문지
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    • 제21권5호
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    • pp.1109-1122
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    • 1996
  • Generally, moving images contain the various components in motions, which reange from a static object and background to a fast moving object. To extract the accurate motion parameters, we must consider the various motions. That requires a wide search egion in motion estimation. The wide search, however, causes a high computational complexity. If we have a few knowledge about the motion direction and magnitude before motion estimation, we can determine the search location and search window size using the already-known information about the motion. In this paper, we present a local adaptive motion estimation approach that predicts a block motion based on spatio-temporal neighborhood blocks and adaptively defines the search location and search window size. This paper presents a technique for reducing computational complexity, while having high accuracy in motion estimation. The proposed algorithm is introduced the forward and backward projection techniques. The search windeo size for a block is adaptively determined by previous motion vectors and prediction errors. Simulations show significant improvements in the qualities of the motion compensated images and in the reduction of the computational complexity.

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Likelihood search method with variable division search

  • Koga, Masaru;Hirasawa, Kotaro;Murata, Junichi;Ohbayashi, Masanao
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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    • pp.14-17
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    • 1995
  • Various methods and techniques have been proposed for solving optimization problems; the methods have been applied to various practical problems. However the methods have demerits. The demerits which should be covered are, for example, falling into local minima, or, a slow convergence speed to optimal points. In this paper, Likelihood Search Method (L.S.M.) is proposed for searching for a global optimum systematically and effectively in a single framework, which is not a combination of different methods. The L.S.M. is a sort of a random search method (R.S.M.) and thus can get out of local minima. However exploitation of gradient information makes the L.S.M. superior in convergence speed to the commonly used R.S.M..

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Fault Detection and Classification with Optimization Techniques for a Three-Phase Single-Inverter Circuit

  • Gomathy, V.;Selvaperumal, S.
    • Journal of Power Electronics
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    • 제16권3호
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    • pp.1097-1109
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    • 2016
  • Fault detection and isolation are related to system monitoring, identifying when a fault has occurred, and determining the type of fault and its location. Fault detection is utilized to determine whether a problem has occurred within a certain channel or area of operation. Fault detection and diagnosis have become increasingly important for many technical processes in the development of safe and efficient advanced systems for supervision. This paper presents an integrated technique for fault diagnosis and classification for open- and short-circuit faults in three-phase inverter circuits. Discrete wavelet transform and principal component analysis are utilized to detect the discontinuity in currents caused by a fault. The features of fault diagnosis are then extracted. A fault dictionary is used to acquire details about transistor faults and the corresponding fault identification. Fault classification is performed with a fuzzy logic system and relevance vector machine (RVM). The proposed model is incorporated with a set of optimization techniques, namely, evolutionary particle swarm optimization (EPSO) and cuckoo search optimization (CSO), to improve fault detection. The combination of optimization techniques with classification techniques is analyzed. Experimental results confirm that the combination of CSO with RVM yields better results than the combinations of CSO with fuzzy logic system, EPSO with RVM, and EPSO with fuzzy logic system.

Estimation of Manoeuvring Coefficients of a Submerged Body using Parameter Identification Techniques

  • Kim, Chan-Ki;Rhee, Key-Pyo
    • Journal of Hydrospace Technology
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    • 제2권2호
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    • pp.24-35
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    • 1996
  • This paper describes parameter identification techniques formulated for the estimation of maneuvering coefficients of a submerged body. The first part of this paper is concerned with the identifiability of the system parameters. The relationship between a stochastic linear time-invariant system and the equivalent dynamic system is investigated. The second is concerned with the development of the numerically stable identification technique. Two identification techniques are tested; one is the ma7mum likelihood (ML) methods using the Holder & Mead simplex search method and using the modified Newton-Raphson method, and the other is the modified extended Kalman filter (MEKF) method with a square-root algorithm, which can improve the numerical accuracy of the extended Kalman filter. As a results, it is said that the equations of motion for a submerged body have higher probability to generate simultaneous drift phenomenon compared to general state equations and only the ML method using the Holder & Mead simplex search method and the MEKF method with a square-root algorithm gives acceptable results.

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Effectiveness of Cognitive Behavioral Therapy Techniques for Control of Pain in Lung Cancer Patients: An Integrated Review

  • Phianmongkhol, Yupin;Thongubon, Kannika;Woottiluk, Pakapan
    • Asian Pacific Journal of Cancer Prevention
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    • 제16권14호
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    • pp.6033-6038
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    • 2015
  • Background: Experience of lung cancer includes negative impacts on both physical and psychological health. Pain is one of the negative experiences of lung cancer. Cognitive behavioral therapy techniques are often recommended as treatments for lung cancer pain. The objective of this review was to synthesize the evidence on the effectiveness of cognitive behavioral therapy techniques in treating lung cancer pain. This review considered studies that included lung cancer patients who were required to 1) be at least 18 years old; 2) speak and read English or Thai; 3) have a life expectancy of at least two months; 4) experience daily cancer pain requiring an opioid medication; 5) have a positive response to opioid medication; 6) have "average or usual" pain between 4 and 7 on a scale of 0-10 for the day before the clinic visit or for a typical day; and 7) able to participate in a pain evaluation and treatment program. This review considered studies to examine interventions for use in treatment of pain in lung cancer patients, including: biofeedback, cognitive/attentional distraction, imagery, hypnosis, and meditation. Any randomized controlled trials (RCTs) that examined cognitive behavioral therapy techniques for pain specifically in lung cancer patients were included. In the absence of RCTs, quasi-experimental designs were reviewed for possible conclusion in a narrative summary. Outcome measures were pain intensity before and after cognitive behavioural therapy techniques. The search strategy aimed to find both published and unpublished literature. A three-step search was utilised by using identified keywords and text term. An initial limited search of MEDLINE and CINAHL was undertaken followed by analysis of the text words contained in the title and abstract, and of the index terms used to describe the article. A second search using all the identified keywords and index terms was then undertaken across all included databases. Thirdly, the reference list of all identified reports and articles were searched for additional studies. Searches were conducted during January 1991- March 2014 limited to English and Thai languages with no date restriction. Materials and Methods: All studies that met the inclusion criteria were assessed for methodological quality by three reviewers using a standardized critical appraisal tool from the Joanna Briggs Institute (JBI). Three reviewers extracted data independently, using a standardized data extraction tool from the Joanna Briggs Institute (JBI). Ideally for quantitative data meta-analysis was to be conducted where all results were subject to double data entry. Odds ratios (for categorical data) and weighted mean differences (for continuous data) and their 95% confidence intervals were to be calculated for analysis and heterogeneity was to be assessed using the standard Chi-square. Where statistical pooling was not possible the finding were be presented in narrative form. Results: There were no studies located that met the inclusion requirements of this review. There were also no text and opinion pieces that were specific to cognitive behavioral therapy techniques pain and lung cancer patients.Conclusions: There is currently no evidence available to determine the effectiveness of cognitive behavioural therapy techniques for pain in lung cancer patients.

AI 기반 설계 탐색 기법을 통한 선박의 주요 치수 최적화 (A Study on the Optimization of Main Dimensions of a Ship by Design Search Techniques based on the AI)

  • 박동우;김인섭
    • 해양환경안전학회지
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    • 제28권7호
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    • pp.1231-1237
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    • 2022
  • 본 논문에서는 AI 기반 설계 탐색 기법을 활용하여 선박의 주요 치수 최적화를 수행하였다. 설계 탐색 기법은 최적화 프로그램 HEEDS의 SHERPA 알고리즘을 사용하였다. 유동 해석은 상용 CFD 코드인 STAR-CCM+를 사용하였고, 주요 치수 변환은 전처리 과정에서 JAVA Script와 Python을 사용하여 선박의 치수가 자동으로 변환되도록 설정하였다. 대상 선박은 소형 쌍동선형으로 주요 치수 최적화는 한쪽 선형의 길이, 폭, 흘수 그리고 단동선형 간의 간격에 대하여 수행되었다. 최적화 알고리즘에 사용된 목적함수는 총저항이며, 내부 의장 시스템의 크기 등을 고려한 배수 체적의 범위를 제한조건으로 선정하였다. 그 결과 최적 선형의 주요 치수는 기존 선형 대비 ±5% 내에서 변화가 있었고 총저항은 약 11% 개선된 결과를 보였다. 본 연구를 통해 선박의 형상을 직접 변경하지 않더라도 주요 치수 최적화를 통해 선박의 저항 성능이 향상됨을 확인하였고, 다양한 선박의 주요 치수 최적화를 통한 성능 향상에 활용이 될 것으로 기대한다.

신경생리학적(神經生理學的) 동물실험(動物實驗)의 기초(基礎) (Techniques for the Neurophysiological Experiments of Brain and Behavior)

  • 전진숙
    • 수면정신생리
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    • 제1권2호
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    • pp.145-155
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    • 1994
  • The neurophysiological study has been widely used in the search of the relation between brain and behavior. The basic techniques for the animal experiments of this kind such as stereotaxic techniques, lesioning methods, the methods of electrical stimulation and confirmation of histological location were simply reviewed. Nevertheless, the importance of complementary neurochemical, neuroanatomical and behavioral studies can not be neglected.

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An Adaptive Block Matching Algorithm based on Temporal Correlations

  • Yoon, Hyo-Sun;Son, Nam-Rye;Lee, Guee-Sang;Kim, Soo-Hyung
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -1
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    • pp.188-191
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    • 2002
  • To reduce the bit-rate of video sequences by removing temporal redundancy, motion estimation techniques have been developed. However, the high computational complexity of the problem makes such techniques very difficult to be applied to high-resolution applications in a real time environment. For this reason, low computational complexity motion estimation algorithms are viable solutions. If a priori knowledge about the motion of the current block is available before the motion estimation, a better starting point for the search of n optimal motion vector on be selected and also the computational complexity will be reduced. In this paper, we present an adaptive block matching algorithm based on temporal correlations of consecutive image frames that defines the search pattern and the location of initial starting point adaptively to reduce computational complexity. Experiments show that, comparing with DS(Diamond Search) algorithm, the proposed algorithm is about 0.1∼0.5(㏈) better than DS in terms of PSNR and improves as much as 50% in terms of the average number of search points per motion estimation.

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유전자 알고리즘을 이용한 차량 승차감 개선에 관한 연구 (A Study on the Improvement of Vehicle Ride Comfort by Genetic Algorithms)

  • 백운태;성활경
    • 한국자동차공학회논문집
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    • 제6권4호
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    • pp.76-85
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    • 1998
  • Recently, Genetic Algorithm(GA) is widely adopted into a search procedure for structural optimization, which is a stochastic direct search strategy that mimics the process of genetic evolution. This methods consist of three genetics operations maned selection, crossover and mutation. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA, being zero-order method, is very simple. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher probability of converge to global optimum compared to traditional techniques which take one-point search method. In this study, a method of finding the optimum values of suspension parameters is proposed by using the GA. And vehicle is modelled as planar vehicle having 5 degree-of-freedom. The generalized coordinates are vertical motion of passenger seat, sprung mass and front and rear unsprung mass and rotate(pitch) motion of sprung mass. For rapid converge and precluding local optimum, share function which distribute chromosomes over design bound is introduced. Elitist survival model, remainder stochastic sampling without replacement method, multi-point crossover method are adopted. In the sight of the improvement of ride comfort, good result can be obtained in 5-D.O.F. vehicle model by using GA.

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