Results 261 to 270 of about 80,774 (312)
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Opposition-Based Differential Evolution Algorithms
2006 IEEE International Conference on Evolutionary Computation, 2006Evolutionary Algorithms (EAs) are well-known optimization approaches to cope with non-linear, complex problems. These population-based algorithms, however, suffer from a general weakness; they are computationally expensive due to slow nature of the evolutionary process.
S. Rahnamayan +2 more
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Cellular Differential Evolution Algorithm
2010This paper presents a cellular version of Differential Evolution (DE) algorithm. The notion behind the geographical distribution of DE population with local interaction is to study the influence of slow diffusion of information throughout the population.
Nasimul Noman, Hitoshi Iba
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Multi-search differential evolution algorithm
Applied Intelligence, 2017The differential evolution algorithm (DE) has been shown to be a very simple and effective evolutionary algorithm. Recently, DE has been successfully used for the numerical optimization. In this paper, first, based on the fitness value of each individual, the population is partitioned into three subpopulations with different size.
Xiangtao Li, Shijing Ma, Jiehua Hu
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An adaptive differential evolution algorithm
2011 IEEE Congress of Evolutionary Computation (CEC), 2011The performance of Differential Evolution (DE) algorithm is significantly affected by its parameter setting. But the choice of parameters is heavily dependent on the problem characteristics. Therefore, recently a couple of adaptation schemes that automatically adjust DE parameters have been proposed.
Nasimul Noman +2 more
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Auto Adaptive Differential Evolution Algorithm
2019 3rd International Conference on Computing Methodologies and Communication (ICCMC), 2019Differential Evolution algorithm has proved to be effective and best method for solving various optimization challenges. It has been proved to be rather cumbersome to manually set control parameters in DE. This paper sketch a new variant of the DE algorithm that provides an environment to auto-adjust the control parameters settings. For the past years,
Vivek Sharma +2 more
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Parameter Selection of Differential Evolution by another Differential Evolution Algorithm
2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), 2019The performance of differential evolution (DE) highly depends on its control parameters, especially for the first proposed simple or standard DE. Control parameters suitable for one objective function are generally not beneficial to another. To automatically find out optimal control parameter settings for different objective functions, we propose a ...
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Differential Evolution Algorithm for Dynamic Structural Identification
Journal of Earthquake Engineering, 2008In the present article, differential evolution algorithm is used to perform structural identification of mass and stiffness properties of civil structures from dynamic test results. Identification is performed initially starting from exact values of modal parameters (frequencies and mode shapes).
SAVOIA, MARCO, VINCENZI, LORIS
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Data Classification Algorithm Based on Differential Evolution Algorithm
International Journal of Digital Content Technology and its Applications, 2013K-Nearest Neighbor (KNN) is one of the most popular algorithms for data classification. Many researchers have found that the KNN algorithm accomplishes very good performance in their experiments on different datasets. The traditional KNN text classification algorithm has limitations: calculation complexity, the performance is solely dependent on the ...
Xuesong Yan - +3 more
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Differential evolution versus genetic algorithms
Proceedings of the 16th International Database Engineering & Applications Sysmposium on - IDEAS '12, 2012The differential evolution (DE) is a very powerful search method for solving many optimization problems. In this paper we present a new scheme (DESAX) based on the differential evolution to localize the breakpoints utilized with the symbolic aggregate approximation method; one of the most important symbolic representation techniques for times series ...
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Effective competency based differential evolution algorithm
Journal of Statistics and Management Systems, 2019AbstractThe DE algorithm is considered as an efficient algorithm in the field of evolutionary algorithms.
Prashant Sharma +2 more
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