An Efficient Algorithm for Minimizing Multi Non-Smooth Component Functions by Minh Pham (2458399)

“…We propose an algorithm to minimize this type of objective functions based on the idea of alternating linearization. …”

Parameters of the test function. by Yiqiong Gao (16698968)

“…The adaptive adjustment of the transition probability effectively balances the development and exploration abilities of the algorithm. The improved flower pollination algorithm (IFPA) outperformed six classical benchmark functions that were used to verify the superiority of the improved algorithm. …”

Feature selection algorithm. by Mahmoud Zeydabadinezhad (12289570)

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Details of S-shaped and V-shaped functions. by Yan Wei (32168)

“…The training data were input to the support vector machine for prediction. The proposed method is experimented by comparing it with peers, well-known machine learning models on the IEEE CEC2017 benchmark functions, public datasets, and graduate employment prediction dataset. …”

Table_1_Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models.DOCX by Shakiru A. Alaka (9302864)

“…We evaluate the predictive accuracy of machine-learning algorithms for predicting functional outcomes in acute ischemic stroke patients after endovascular treatment.…”

Automated diagnosis of heart valve degradation using novelty detection algorithms and machine learning by Bernhard Vennemann (7434353)

“…Heart valves are subject to high hydrodynamic loads which render them prone to premature degradation. …”

Pipeline of the interactor algorithm. by Jose Cleydson F. Silva (8685594)

Data_Sheet_1_Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models.PDF by Shakiru A. Alaka (9302864)

“…We evaluate the predictive accuracy of machine-learning algorithms for predicting functional outcomes in acute ischemic stroke patients after endovascular treatment.…”

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

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Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

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List of selected ranges of movements(ROM), from which features were then counted. by Jindřich Adolf (17334216)

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Details of 23 basic benchmark functions. by Ying Li (38224)

Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

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Data_Sheet_1_Modeling Macroscopic Material Behavior With Machine Learning Algorithms Trained by Micromechanical Simulations.CSV by Denise Reimann (7213364)

Data_Sheet_2_Modeling Macroscopic Material Behavior With Machine Learning Algorithms Trained by Micromechanical Simulations.pdf by Denise Reimann (7213364)

IEEE CEC 2017 benchmark function specifications. by Kankan Tang (21474968)

IEEE CEC 2022 benchmark function specifications. by Kankan Tang (21474968)

Myosoft: An automated muscle histology analysis tool using machine learning algorithm utilizing FIJI/ImageJ software by Lucas Encarnacion-Rivera (8532147)

IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

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IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

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