Search alternatives:
within function » fibrin function (Expand Search), python function (Expand Search), protein function (Expand Search)
algorithm both » algorithm blood (Expand Search), algorithm b (Expand Search), algorithm etc (Expand Search)
flow function » from function (Expand Search), low functional (Expand Search), loss function (Expand Search)
both function » body function (Expand Search), growth function (Expand Search), beach function (Expand Search)
within function » fibrin function (Expand Search), python function (Expand Search), protein function (Expand Search)
algorithm both » algorithm blood (Expand Search), algorithm b (Expand Search), algorithm etc (Expand Search)
flow function » from function (Expand Search), low functional (Expand Search), loss function (Expand Search)
both function » body function (Expand Search), growth function (Expand Search), beach function (Expand Search)
-
1
Model intrinsic parameter flow.
Published 2025“…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. …”
-
2
-
3
Flow chart diagram of blind quantum algorithm.
Published 2024“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”
-
4
Flow chart diagram of quantum hash function.
Published 2024“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”
-
5
-
6
Completion times for different algorithms.
Published 2025“…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. …”
-
7
The average cumulative reward of algorithms.
Published 2025“…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. …”
-
8
Simulation settings of rMAPPO algorithm.
Published 2025“…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. …”
-
9
Comparison of different algorithms.
Published 2025“…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. …”
-
10
Study proposed algorithm.
Published 2025“…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. Invasive coronary assessment has been shown to be both feasible and safe. …”
-
11
Multi-algorithm comparison figure.
Published 2025“…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. …”
-
12
-
13
-
14
-
15
-
16
-
17
-
18
-
19
-
20