The variation of a with t (take T = 100 for example). by Yi-Qiang Xia (20161326)

Horizontal central profiles produced for the 128-th row of the restored images with different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10<sup>−3</su... by Limin Ma (556873)

3D profiles of <i>β</i> and λ with respect to the MAE for different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10⁻³. by Limin Ma (556873)

Vertical central profiles produced for the 128-th column of the restored images with different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10<sup>−3</s... by Limin Ma (556873)

Evolution of porosity (<i>ϕ</i>) as a function of rescaled CBL (relative age; ) measured in seal skulls. by Jonathan E Kings (20818367)

Test results of multimodal benchmark functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Fixed-dimensional multimodal reference functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Test results of multimodal benchmark functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Fitness function over the 50 runs. by Mohammed Alqahtani (2049139)

“…Results reveal that ZOA outperformed other algorithms, supplying electricity at a minimum cost of 0.1285 $/kWh in one configuration, with the LFP battery achieving the lowest NPC of 3.8 M$ in case studies with constrained LPSP. …”

Fitness function over the 50 runs. by Mohammed Alqahtani (2049139)

“…Results reveal that ZOA outperformed other algorithms, supplying electricity at a minimum cost of 0.1285 $/kWh in one configuration, with the LFP battery achieving the lowest NPC of 3.8 M$ in case studies with constrained LPSP. …”

Fitness function over the 50 runs. by Mohammed Alqahtani (2049139)

“…Results reveal that ZOA outperformed other algorithms, supplying electricity at a minimum cost of 0.1285 $/kWh in one configuration, with the LFP battery achieving the lowest NPC of 3.8 M$ in case studies with constrained LPSP. …”

S- and V-Type transfer function diagrams. 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. …”

Boxplot of en-CSA compared to CSA, CGO, HHO, SSA, GTO, WOA, PSO, and TSA using benchmark functions. by Sarah A. Alzakari (19704611)

Convergence of en-CSA compared to CSA, CGO, HHO, SSA, GTO, WOA, PSO, and TSA using benchmark functions. by Sarah A. Alzakari (19704611)

Comparison between the non-sensory motor and sensory–motor algorithms. by Hiroyuki Ichijo (13891153)

Learning alters pirouette decision and behavioral noise. by Kevin S. Chen (9201767)

PATH (with persistence fingerprint) runs significantly faster than TNet-BP, a representative binding affinity prediction algorithm that uses persistent homology, on larger protein-... by Yuxi Long (11024307)

Model-based decoding of learning. by Kevin S. Chen (9201767)

Degree 5 algorithm from Recovering the cluster picture of a polynomial over a discretely valued field by Lilybelle Cowland Kellock (20938306)

The cost function Φ(<i>x</i>, <i>w</i>) versus the number of iterations for different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10⁻³.... by Limin Ma (556873)