Trainable parameters for different algorithms. by Anwar Hossain Efat (19942283)

Functional enrichment analysis of hub genes. by Tingting Liu (267387)

CEC2022 and CEC2017 benchmark functions. by Chengcheng Ding (9013862)

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data by Andreas Tosstorff (8250999)

Subjects:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data by Andreas Tosstorff (8250999)

Subjects:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data by Andreas Tosstorff (8250999)

Subjects:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data by Andreas Tosstorff (8250999)

Subjects:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data by Andreas Tosstorff (8250999)

Subjects:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data by Andreas Tosstorff (8250999)

Subjects:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data by Andreas Tosstorff (8250999)

Subjects:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data by Andreas Tosstorff (8250999)

Subjects:

Comparison of Molecular Recognition in Docking Versus Experimental CSD and PDB Data by Andreas Tosstorff (8250999)

Subjects:

Flowchart of simple ant colony algorithm. by Yang Yu (4292)

“…This algorithm provides both a primary routing path and an alternate routing path for service transmission, ensuring the delivery of high-priority services even when both the primary and standby paths are unavailable. …”

The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…<div><p>In this paper, we study a class of non-parametric regression models for predicting graph signals as a function of explanatory variables . Recently, Kernel Graph Regression (KGR) and Gaussian Processes over Graph (GPoG) have emerged as promising techniques for this task. …”

Attack and defense behaviors with the sensory–motor algorithm between multiple predators and prey. by Hiroyuki Ichijo (13891153)

Variations of loss functions versus epoch number. by Xueliang Guo (4797057)

The results of gene ontology analysis of the hub genes, including (a) biological process, (b) cellular components, (c) molecular functions, and (d) pathway analysis. by Devi Soorya Narayana Sasikumar (22331743)

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In vitro and in vivo DMS structure probing of ModT isoforms. by Tina Lenče (20428084)

Overall process planning. by Dawei Wang (471687)

“…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”

Model intrinsic parameter flow. by Dawei Wang (471687)

“…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”