Rosenbrock function processing time and deviations from constraint for . by Shikun Chen (14625352)

Rastrigin function processing time and deviations from constraint for . by Shikun Chen (14625352)

Rastrigin function processing time and deviations from constraint for . by Shikun Chen (14625352)

Rosenbrock function processing time and deviations from constraint for . by Shikun Chen (14625352)

Levy function processing time and deviations from constraint for . by Shikun Chen (14625352)

Rastrigin function processing time and deviations from constraint for . by Shikun Chen (14625352)

Rosenbrock function processing time and deviations from constraint for . by Shikun Chen (14625352)

Levy function processing time and deviations from constraint for . by Shikun Chen (14625352)

Comparison of different algorithms. 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. …”

Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

“…Whiskers show the lowest and highest values within 1.5 × <i>IQR</i> from the first and third quartiles, respectively. …”

Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

Subjects:

IEEE CEC 2017 benchmark function specifications. by Kankan Tang (21474968)

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

Study proposed algorithm. by Ainhoa Pérez-Guerrero (21377457)

“…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. …”

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

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

Gillespie algorithm simulation parameters. by Nicholas H. Vitale (20469289)

“…Both the ensemble and stochastic models presented in this work have been verified using Monte Carlo molecular dynamic simulations that utilize the Gillespie algorithm. …”

Scheduling time of five algorithms. by Huichao Guo (14515171)

“…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …”

Convergence speed of five algorithms. by Huichao Guo (14515171)

“…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …”

Reactive Molecular Simulation and Microscopic Origins in the Reaction Kinetics of Binary Polymerization by Xinwei Chen (255125)

“…A microscopic expression of the hybrid function is derived based on the general collision reaction model and reactive algorithm in molecular dynamics (MD) simulation, in which both the reaction energy barrier and intermolecular interaction play pivotal roles. …”