The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

The crack control optimization algorithm. by Shouyan Wu (17101845)

“…It is evident that the optimization algorithm exhibits robustness and stability in the context of crack control, consistently delivering favorable outcomes across diverse parameter configurations.…”

Data_Sheet_1_CLGBO: An Algorithm for Constructing Highly Robust Coding Sets for DNA Storage.docx by Yanfen Zheng (3814507)

“…We made use of the CLGBO algorithm and the non-adjacent subsequence constraint to construct larger and more highly robust coding sets.…”

Data and code. by Hao Cao (2248066)

“…These performance metrics indicate a significant improvement over traditional and other deep learning models, confirming the model’s superiority in predictive maintenance of elevators. The robust capability of the VMD-BILSTM-AEAM algorithm to accurately process and analyze time-series data, even in the presence of noise, highlights its potential for broader applications in predictive maintenance and fault detection across various domains.…”

MapRobust by Wangshu Mu (7517315)

Comparison of Pearson correlations and F-measure values of NN-RNALoc algorithm with other methods for two datasets. by Negin Sadat Babaiha (16985907)

Comparison of optimization algorithms and their robustness to noise. by Will Xiao (8975351)

Code and data. by Gongfeng Xin (14059483)

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Overview of the C&CG method. by Tianhe Sun (21145341)

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The output SINR versus the number of elements. by Lin Chang (785086)

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Key steps in neurodegeneration detection algorithm. by Andrew S. Clark (16510496)

Comparison of planning results for different uncertainty quantification methods. by Tianhe Sun (21145341)

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Robust optimization through neuroevolution by Paolo Pagliuca (5532746)

“…The comparison of different algorithms indicates that the CMA-ES and xNES methods, that operate by optimizing a distribution of parameters, represent the best options for the evolution of robust neural network controllers.…”

Optimization flowchart of dung beetle optimization algorithm. by Xiangfei Tao (20775636)

Image1_RobustTree: An adaptive, robust PCA algorithm for embedded tree structure recovery from single-cell sequencing data.pdf by Ziwei Chen (626412)

The optimization trend for each algorithm. by Yong Dai (108856)

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Optimality of the algorithm (REA). by Wuyang Yu (1644781)

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Robust optimization through neuroevolution - Fig 4 by Paolo Pagliuca (5532746)

Robustness of VMseg parameters optimization process. by Hugo LE BOITE (19346610)

Elements of the spectral estimation algorithm. by Mark D. Humphries (11068147)