This article proposes two optimization schemes for the position of elements in sparse circular spherical array with low sidelobes based on genetic algorithm. The first optimization scheme is to first optimize the radi...
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This paper investigates the online distributed optimization problem. First, we propose a novel gradient descent algorithm without a central node under a multi-agent network. Second, the regret with forgetting-factor i...
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Evolutionary computation algorithms have been extensively studied to locate multiple global peaks in multimodal optimization problems (MMOPs). However, multitask multimodal optimization, which aims to deal with multip...
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Problem transformation based optimization for large-scale multi-objective problems usually have excellent con-vergence yet insufficient diversity. Improving the distributivity of the search subspace in the decision sp...
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The traditional path planning problems typically focus on a single objective, whereas in the field of Wargame, it is crucial to consider trade-offs and compromises between multiple objectives. To address this issue, w...
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This study explores the effectiveness of the traditional Firefly algorithm (FA) in optimizing the Gaussian Kernel-based Fuzzy C-means clustering (GKFCM) algorithm by adjusting 'sigma' and 'm'. We compa...
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In the rapidly developing field of information technology today, the optimization of neural network algorithms has become a common focus of attention in both academia and industry. Especially when dealing with complex...
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This paper proposes a k-means algorithm enhanced with GEO (Golden Eagle Optimizer) optimization to address the challenges encountered by traditional k-means algorithm, such as being highly sensitive to initial values ...
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At present, with the continuous increase of Internet users in rural China, the scale of online shopping is also expanding, and the development prospect of rural e-commerce is obvious. The scattered rural population an...
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Leveraging on fruitful intertask knowledge transfer, multitasking evolutionary algorithms (MTEAs) exhibit superior efficiency in handling multiple optimization tasks simultaneously. In practice, it is common that the ...
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