• Title/Summary/Keyword: Random algorithm

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FUZZY NONLINEAR RANDOM VARIATIONAL INCLUSION PROBLEMS INVOLVING ORDERED RME-MULTIVALUED MAPPING IN BANACH SPACES

  • Kim, Jong Kyu;Salahuddin, Salahuddin
    • East Asian mathematical journal
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    • v.34 no.1
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    • pp.47-58
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    • 2018
  • In this paper, we consider a fuzzy nonlinear random variational inclusion problems involving ordered RME-multivalued mapping in ordered Banach spaces. By using the random relaxed resolvent operator and its properties, we suggest an random iterative algorithm. Finally both the existence of the random solution of the original problem and the convergence of the random iterative sequences generated by random algorithm are proved.

Optimum Allocation of Pipe Support Using Combined Optimization Algorithm by Genetic Algorithm and Random Tabu Search Method (유전알고리즘과 Random Tabu 탐색법을 조합한 최적화 알고리즘에 의한 배관지지대의 최적배치)

  • 양보석;최병근;전상범;김동조
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.3
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    • pp.71-79
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    • 1998
  • This paper introduces a new optimization algorithm which is combined with genetic algorithm and random tabu search method. Genetic algorithm is a random search algorithm which can find the global optimum without converging local optimum. And tabu search method is a very fast search method in convergent speed. The optimizing ability and convergent characteristics of a new combined optimization algorithm is identified by using a test function which have many local optimums and an optimum allocation of pipe support. The caculation results are compared with the existing genetic algorithm.

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Maximal overlap discrete wavelet transform-based power trace alignment algorithm against random delay countermeasure

  • Paramasivam, Saravanan;PL, Srividhyaa Alamelu;Sathyamoorthi, Prashanth
    • ETRI Journal
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    • v.44 no.3
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    • pp.512-523
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    • 2022
  • Random delay countermeasures introduce random delays into the execution flow to break the synchronization and increase the complexity of the side channel attack. A novel method for attacking devices with random delay countermeasures has been proposed by using a maximal overlap discrete wavelet transform (MODWT)-based power trace alignment algorithm. Firstly, the random delay in the power traces is sensitized using MODWT to the captured power traces. Secondly, it is detected using the proposed random delay detection algorithm. Thirdly, random delays are removed by circular shifting in the wavelet domain, and finally, the power analysis attack is successfully mounted in the wavelet domain. Experimental validation of the proposed method with the National Institute of Standards and Technology certified Advanced Encryption Standard-128 cryptographic algorithm and the SAKURA-G platform showed a 7.5× reduction in measurements to disclosure and a 3.14× improvement in maximum correlation value when compared with similar works in the literature.

ITERATIVE ALGORITHM FOR RANDOM GENERALIZED NONLINEAR MIXED VARIATIONAL INCLUSIONS WITH RANDOM FUZZY MAPPINGS

  • Faizan Ahmad, Khan;Eid Musallam, Aljohani;Javid, Ali
    • Nonlinear Functional Analysis and Applications
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    • v.27 no.4
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    • pp.881-894
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    • 2022
  • In this paper, we consider a class of random generalized nonlinear mixed variational inclusions with random fuzzy mappings and random relaxed cocoercive mappings in real Hilbert spaces. We suggest and analyze an iterative algorithm for finding the approximate solution of this class of inclusions. Further, we discuss the convergence analysis of the iterative algorithm under some appropriate conditions. Our results can be viewed as a refinement and improvement of some known results in the literature.

A Study on Adaptive Random Signal-Based Learning Employing Genetic Algorithms and Simulated Annealing (유전 알고리즘과 시뮬레이티드 어닐링이 적용된 적응 랜덤 신호 기반 학습에 관한 연구)

  • Han, Chang-Wook;Park, Jung-Il
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.10
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    • pp.819-826
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    • 2001
  • Genetic algorithms are becoming more popular because of their relative simplicity and robustness. Genetic algorithms are global search techniques for nonlinear optimization. However, traditional genetic algorithms, though robust, are generally not the most successful optimization algorithm on any particular domain because they are poor at hill-climbing, whereas simulated annealing has the ability of probabilistic hill-climbing. Therefore, hybridizing a genetic algorithm with other algorithms can produce better performance than using the genetic algorithm or other algorithms independently. In this paper, we propose an efficient hybrid optimization algorithm named the adaptive random signal-based learning. Random signal-based learning is similar to the reinforcement learning of neural networks. This paper describes the application of genetic algorithms and simulated annealing to a random signal-based learning in order to generate the parameters and reinforcement signal of the random signal-based learning, respectively. The validity of the proposed algorithm is confirmed by applying it to two different examples.

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A rubber o-ring defect detection system using data augmentation based on the SinGAN and random forest algorithm (SinGAN기반 데이터 증강과 random forest알고리즘을 이용한 고무 오링 결함 검출 시스템)

  • Lee, Yong Eun;Lee, Han Sung;Kim, Dae Won;Kim, Kyung Chun
    • Journal of the Korean Society of Visualization
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    • v.19 no.3
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    • pp.63-68
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    • 2021
  • In this study, data was augmentation through the SinGAN algorithm using small image data, and defects in rubber O-rings were detected using the random forest algorithm. Unlike the commonly used data augmentation image rotation method to solve the data imbalance problem, the data imbalance problem was solved by using the SinGAN algorithm. A study was conducted to distinguish between normal products and defective products of rubber o-ring by using the random forest algorithm. A total of 20,000 image date were divided into transit and testing datasets, and an accuracy result was obtained to distinguish 97.43% defects as a result of the test.

Random Order Chart Parsing Algorithm (임의 순서 차트 파싱 알고리즘)

  • Shim, Kwang-Seob
    • Journal of KIISE:Software and Applications
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    • v.37 no.6
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    • pp.446-454
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    • 2010
  • According to the original chart parsing algorithm, a sentence is parsed in a strict left-to-right order. The modified chart parsing algorithm proposed in this paper breaks the strictness. With the proposed algorithm, a sentence is parsed in a random order. Conventional left-to-right parsing is also possible, since left-to-right parsing is a special case of random-order parsing. The proposed parsing algorithm is an extension of chart parsing algorithm and its control structure is very simple, so that it is easy to implement the algorithm.

Development of an Enhanced Artificial Life Optimization Algorithm and Optimum Design of Short Journal Bearings (향상된 인공생명 최적화 알고리듬의 개발과 소폭 저널 베어링의 최적설계)

  • Yang, Bo-Suk;Song, Jin-Dae
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.12 no.6
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    • pp.478-487
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    • 2002
  • This paper presents a hybrid method to compute the solutions of an optimization Problem. The present hybrid algorithm is the synthesis of an artificial life algorithm and the random tabu search method. The artificial life algorithm has the most important feature called emergence. The emergence is the result of dynamic interaction among the individuals consisting of the system and is not found in an individual. The conventional artificial life algorithm for optimization is a stochastic searching algorithm using the feature of artificial life. Emergent colonies appear at the optimum locations in an artificial ecology. And the locations are the optimum solutions. We combined the feature of random-tabu search method with the conventional algorithm. The feature of random-tabu search method is to divide any given region into sub-regions. The enhanced artificial life algorithm (EALA) not only converge faster than the conventional artificial life algorithm, but also gives a more accurate solution. In addition, this algorithm can find all global optimum solutions. The enhanced artificial life algorithm is applied to the optimum design of high-speed, short journal bearings and its usefulness is verified through an optimization problem.

FUZZY GENERAL NONLINEAR ORDERED RANDOM VARIATIONAL INEQUALITIES IN ORDERED BANACH SPACES

  • Salahuddin, Salahuddin;Lee, Byung-Soo
    • East Asian mathematical journal
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    • v.32 no.5
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    • pp.685-700
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    • 2016
  • The main object of this work to introduced and studied a new class of fuzzy general nonlinear ordered random variational inequalities in ordered Banach spaces. By using the random B-restricted accretive mapping with measurable mappings ${\alpha},{\alpha}^{\prime}:{\Omega}{\rightarrow}(0,1)$, an existence of random solutions for this class of fuzzy general nonlinear ordered random variational inequality (equation) with fuzzy mappings is established, a random approximation algorithm is suggested for fuzzy mappings, and the relation between the first value $x_0(t)$ and the random solutions of fuzzy general nonlinear ordered random variational inequality is discussed.

Adaptive Random Access Algorithm for HIPERLAN/2 (HIPERLAN/2를 위한 적응적 랜덤 액세스 알고리즘)

  • Song Young-keum;Lee Jong-kyu
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.5B
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    • pp.310-316
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    • 2005
  • In this paper, we proposed and evaluated ARAH(Adaptive Random Access algorithm for HIPERLAN/2) to improve system performance. In this paper, HIPERLAN/2 uses OFDM(Orthogonal Frequency Division Multiplexing) modulation scheme to select appropriate PHY mode by Radio Channel Quality, Proposed the ARAH scheme uses these 7 PHY mode when mobile terminal determines the RCH(Random CHannel) number for random access. In this paper, these 7 PHY mode divided into two group, good and bad, and will be given high priority to mobile terminals which are in a good group. In the result of performance evaluation. ARAH algorithm, ARAH has a better performance of throughput and delay than existing algorithm.