Accumulated model results for daily COVID-19 caused deaths for all the simulations performed during the iterative optimization. by Martin Bicher (10852788)

CT prediction models results. by Amirmohammad Shahbandegan (14265549)

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Membership function of each target. by Tianrui Zhang (2294542)

ROC curves of single feature models. by Amirmohammad Shahbandegan (14265549)

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

“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”

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

“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”

Model coefficients for each feature. by Amirmohammad Shahbandegan (14265549)

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Hyperparameters search space and the top five best-performing models. by Amirmohammad Shahbandegan (14265549)

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Variable performance in 250 top-performing models and the subset of 12 models selected from these used to create the final projections for the predicted habitat distributions of Te... by Elise Varaela Voltura (17592996)

I-NSGA-II-RF algorithm. by Xiaohua Zeng (793632)

“…The integrated information initialization population of two filtered feature selection methods is used to optimize the I-NSGA-II algorithm, using multiple chromosome hybrid coding to synchronously select features and optimize model parameters. …”

The pareto front obtained by each algorithm. by Xiaohua Zeng (793632)

“…The integrated information initialization population of two filtered feature selection methods is used to optimize the I-NSGA-II algorithm, using multiple chromosome hybrid coding to synchronously select features and optimize model parameters. …”

Model integration into the IT system to predict CT exams. by Amirmohammad Shahbandegan (14265549)

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Image_1_On the Use of a Multimodal Optimizer for Fitting Neuron Models. Application to the Cerebellar Granule Cell.TIF by Milagros Marín (7858850)

“…Also, the set of selected cerebellar GrC models captured spiking dynamics closer to the reference model than the single model obtained with off-the-shelf parameter optimization algorithms used in our previous article. …”

The whole test dataset [2]. by Daihong Li (14642581)

The training dataset used in this work [2]. by Daihong Li (14642581)

Simulated trajectories from real data, optimal schedule, and nearest optimal schedule. by Samuel Christensen (9922554)

Experimental parameter settings. by Jiayue Zhang (7832669)

“…In this study, the hybrid model CMNS-YOLO, which combines the crawfish optimization algorithm with the MNS-YOLO model, is proposed to achieve the ultimate detection accuracy. …”

Structure of MNS-YOLO. by Jiayue Zhang (7832669)

“…In this study, the hybrid model CMNS-YOLO, which combines the crawfish optimization algorithm with the MNS-YOLO model, is proposed to achieve the ultimate detection accuracy. …”

Values used to build graphs. by Jiayue Zhang (7832669)

“…In this study, the hybrid model CMNS-YOLO, which combines the crawfish optimization algorithm with the MNS-YOLO model, is proposed to achieve the ultimate detection accuracy. …”

Minimal data set. by Jiayue Zhang (7832669)

“…In this study, the hybrid model CMNS-YOLO, which combines the crawfish optimization algorithm with the MNS-YOLO model, is proposed to achieve the ultimate detection accuracy. …”