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

The benchmark functions. by Shuhui Yu (1535500)

Overview of archaic SNPs (aSNPs) potentially affecting G4 formation, identified by G4SNVHunter. by Rongxin Zhang (1618159)

G4SNVHunter workflow for identifying variants that affect G4 formation. by Rongxin Zhang (1618159)

“…<b>(B)</b> Function-level schematic of the G4SNVHunter workflow, showing the relationships between key modules and their data flow. …”

A hypothetical example illustrating the differences between the two assessment modes in G4SNVHunter. by Rongxin Zhang (1618159)

The accuracy of different algorithms for TMD on SHL and HTC datasets. by Rui Li (4631)

Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

Subjects:

Overnight technician routing and scheduling problem with time windows and balanced workloads: a bi-objective zebra optimization algorithm by Abolfazl Gharaei (21803416)

“…The performance evaluation and validation results revealed that the proposed ML-based BOZOA provides very good performance in solving TRSPTWs at a variety of scales with respect to the optimality criteria, including, number of taken iterations, infeasibility, optimality error and complementarity compared with both an exact solver and two inspired algorithms from ZOA.</p> <p><b>Highlights</b></p><p>An ML-based bi-objective zebra optimisation algorithm to treat large-scale TRSPs</p><p>Centroid-based clustering on the population of zebras to avoid bias towards a specific search space</p><p>Making a trade-off between exploration and exploitation of the feasible region in the developed algorithm</p><p>A new MINLP model of a weighted bi-objective TRSP with limited capacity depots</p><p>Workload function, penalty function for lateness, subcontracts, time windows for tasks and breaks</p><p>Experiments using real data to show the performance of the model and solution method</p><p></p> <p>An ML-based bi-objective zebra optimisation algorithm to treat large-scale TRSPs</p> <p>Centroid-based clustering on the population of zebras to avoid bias towards a specific search space</p> <p>Making a trade-off between exploration and exploitation of the feasible region in the developed algorithm</p> <p>A new MINLP model of a weighted bi-objective TRSP with limited capacity depots</p> <p>Workload function, penalty function for lateness, subcontracts, time windows for tasks and breaks</p> <p>Experiments using real data to show the performance of the model and solution method</p>…”

Data Sheet 2_Machine learning algorithm based on combined clinical indicators for the prediction of infertility and pregnancy loss.zip by Rui Zhang (13940)

“…The model for potential pregnancy loss was also developed using five machine learning algorithms and was based on 7 indicators. According to the results obtained from the testing set, the sensitivity was higher than 92.02%, the specificity was higher than 95.18%, the accuracy was higher than 94.34%, and the AUC was higher than 0.972.…”

Data Sheet 1_Machine learning algorithm based on combined clinical indicators for the prediction of infertility and pregnancy loss.docx by Rui Zhang (13940)

“…The model for potential pregnancy loss was also developed using five machine learning algorithms and was based on 7 indicators. According to the results obtained from the testing set, the sensitivity was higher than 92.02%, the specificity was higher than 95.18%, the accuracy was higher than 94.34%, and the AUC was higher than 0.972.…”

Flowchart for the unsupervised SOM algorithm modified from Seifert et al. [56] with permission. by Sergio Montalt-García (17696115)

Screening process for marker genes from 7 DEGs and the diagnostic value of marker genes. by Kaiyi Zhou (2553352)

Schematic representation of selected data from the Allen Institute dataset. by Saeed Mohammadzadeh (13492285)

Longitudinal trajectories of functional network development across the birth transition. by Lanxin Ji (20290942)

“…Stronger RSFC within networks affirms validity of the network clustering algorithm. (B) Functional parcels and networks. (C) Age effect on the ROI-to-ROI functional connectivity. …”

Test function results. by Ruyi Dong (9038174)

“…From the statistical results of mean, best and variance of different algorithms, the LLSKSO algorithm outperforms the other algorithms. …”

Benchmark test functions. by Ruyi Dong (9038174)

“…From the statistical results of mean, best and variance of different algorithms, the LLSKSO algorithm outperforms the other algorithms. …”

Algorithm parameters. by Ruyi Dong (9038174)

“…From the statistical results of mean, best and variance of different algorithms, the LLSKSO algorithm outperforms the other algorithms. …”

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

Subjects:

Data Sheet 1_Multi-omics analysis and metastasis risk factor prediction in N1b stage PTMC: insights into immune infiltration and therapeutic implications.docx by Hao Dai (4277254)

CEC2017 basic functions. by Tengfei Ma (597633)

“…The optimal individual’s position is updated by randomly selecting from these factors, enhancing the algorithm’s ability to attain the global optimum and increasing its overall robustness. …”