2022
DOI: 10.1109/access.2022.3203695
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Clustering of Typical Wind Power Scenarios Based on K-Means Clustering Algorithm and Improved Artificial Bee Colony Algorithm

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Cited by 24 publications
(10 citation statements)
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“…The improved algorithm's convergence speed and accuracy were found to be enhanced in three function test results. Yao [21] , improved the algorithm from three aspects: swarm initialization, fitness function, and position update formula, overcoming the randomness of the initial algorithm and susceptibility to local optimal solutions. Inspired by the particle swarm optimization algorithm, Zhu [22] , introduced the global best solution (gbest) information into the solution search equation and proposed an improved ABC algorithm, the GABC algorithm, to improve the development rate of the algorithm.…”
Section: Introductionmentioning
confidence: 99%
“…The improved algorithm's convergence speed and accuracy were found to be enhanced in three function test results. Yao [21] , improved the algorithm from three aspects: swarm initialization, fitness function, and position update formula, overcoming the randomness of the initial algorithm and susceptibility to local optimal solutions. Inspired by the particle swarm optimization algorithm, Zhu [22] , introduced the global best solution (gbest) information into the solution search equation and proposed an improved ABC algorithm, the GABC algorithm, to improve the development rate of the algorithm.…”
Section: Introductionmentioning
confidence: 99%
“…It allows for a detailed analysis of the signal at various levels of granularity. Entropy measures the complexity within these decomposed scales to identify the patterns [15][16][17].…”
Section: Introductionmentioning
confidence: 99%
“…The improved algorithm showed that its convergence speed and accuracy were improved compared to the previous version in three function test results. Yao G et al 26 improved the algorithm from three aspects of bee colony initialization, fitness function, and position update formula, overcoming the randomness and easy local optimal solution defects of the initial algorithm. Zhu G et al 27 , inspired by the particle swarm optimization algorithm, introduced the global optimal solution (gbest) information into the solution search equation, proposing an improved ABC algorithm—GABC algorithm, which improves the algorithm's development rate.…”
Section: Introductionmentioning
confidence: 99%