The instance of MaxCasesAverted and MaxPeaksReduced is a graph <i>G</i> constructed from the given instance of Max k-SI. by Jeffrey Keithley (14626551)

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

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)

An exemplar procedure for activity flow modeling based on the direct and shortest paths at a network density of 15%. by Zhengdong Wang (35299)

“…<b>(</b><b>B</b>-<b>C)</b> Mean shortest path length matrices were derived from the weighted and binary FC matrices using Dijkstra’s algorithm. <b>(</b><b>D</b>-<b>F)</b> The predicted activations of 24 task contrasts by activity flow modeling with the routes of FC, SPL_wei, and SPL_bin, respectively. …”

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

Graphical representation of the diffuse interface approach in one dimension. by Martina Bukač (20161460)

Framework of MAPPO. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …”

The average completion time of each method. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …”

The connection of physical space. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …”

End-to-end data transmission delay. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …”

Production workflow of stiffened H-beams. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …”

Collision risk warning. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …”

Framework of rMAPPO. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …”

Data_and_model_files. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …”

Image Encryption Flow Chart. by Feixian Liu (22477943)

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. …”

A comparison of whether to add a penalty. 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. …”

The interleaved processes. 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. …”