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This requires further research on how intelligent algorithms can be applied to large-scale pessimistic bilevel optimization in the current age of big data. Acknowledgments The work presented in this paper was supported by the National Natural Science Foundation of China (11501233). References 1. A....
Recent advances in glaucoma detection have focused on developing new technologies and methods, such as artificial intelligence and machine learning algorithms, which can analyse retinal images and predict the risk of developing glaucoma3. The manual expansion of detecting fundus images is costly, ...
CMA-ES is one of the most competitive blackbox optimization algorithms, regularly dominating the Black-Box Optimization Benchmarking (BBOB) chal- lenge [11]. For further details on population-based methods, we refer to [28, 138]; we discuss applications to hyperparameter optimization in Sect. ...
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-Based Clustering Mechanisms Several optimization-based clustering algorithms were developed in earlier days such as ant colony optimization (ACO), artificial bee colony optimization (ABCO), fuzzy logic (FL), genetic algorithm (GA), whale algorithm, particle swarm optimization (PSO), and so on. ...
This study aims to assess the performance of algorithms for BEO problems with different properties. The reasons why this study is both timely and valuable are multi-folds. Firstly, the properties of BEO problems are essential to the performance of algorithms. Secondly, current research on the ...
Weighted Evaluation of Wind Power Forecasting Models Using Evolutionary Optimization Algorithms. Procedia Comput. Sci. 2017, 114, 357–365. [CrossRef] 25. Pawlak, Z. Rough sets. Int. J. Comput. Inf. Sci. 1982, 11, 341–356. [CrossRef] 26. Pawlak, Z. Rough Set Theory and Its ...
As a result, both algorithms pick these hubs as single node communities resulting in poorer performance. On the other hand, generative models such as SBM performed poorly, mainly when datasets such as Cora and PubMed are used. Since SBM does not support features, it is difficult for SBM to...
These techniques are used to find high-quality solutions that are based on the best possible computing structure [28]. Several advanced strategies (including parallel compu- tation, multi-agent systems, and decomposition of the search space) [29] are often used in hybrid metaheuristic algorithms. ...