Feature selection algorithm. by Mahmoud Zeydabadinezhad (12289570)

Subjects:

Completion times for different algorithms. 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 effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”

The average cumulative reward of algorithms. 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 effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”

Construction of the PRG score index using integrated machine learning algorithms. by Xiangxin Wu (22320058)

Algorithm detection steps. by José M. Rivera-Arbeláez (12418512)

EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

“…Functional groups are widely used in organic chemistry, because they provide a rationale to analyze physicochemical and reactivity properties. …”

Summary of results of naïve Bayes algorithms. by Christopher E. Niemczak (8586861)

Subjects:

Pseudo algorithm of the GA algorithm used in this study. by Tuan Anh Pham (1346049)

Simulation settings of rMAPPO algorithm. 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 effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”

The pseudocode for the NAFPSO algorithm. by Huichao Guo (14515171)

“…A scheduling optimization model based on the particle swarm optimization (PSO) algorithm is proposed. In view of the high-dimensional complexity and local optimal problems, the neighborhood adaptive constrained fractional particle swarm optimization (NACFPSO) algorithm is used to solve it. …”

PSO algorithm flowchart. by Huichao Guo (14515171)

“…A scheduling optimization model based on the particle swarm optimization (PSO) algorithm is proposed. In view of the high-dimensional complexity and local optimal problems, the neighborhood adaptive constrained fractional particle swarm optimization (NACFPSO) algorithm is used to solve it. …”

Continuous Probability Distributions generated by the PIPE Algorithm by LUIS G.B. PINHO (14073372)

“…<div><p>Abstract We investigate the use of the Probabilistic Incremental Programming Evolution (PIPE) algorithm as a tool to construct continuous cumulative distribution functions to model given data sets. …”

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. …”

Flowchart for Algorithm 1. by Sagvan Y. Musa (17797611)

Flowchart for Algorithm 2. by Sagvan Y. Musa (17797611)

Standard functions to test. by Kemal Gökhan Nalbant (18858009)

Iteration curves of different algorithms. by Tengfei Ma (597633)

Subjects:

Flowchart of OP-ZOA algorithm. by Tengfei Ma (597633)

Subjects:

Optimum feature set for classification using both core and margin information utilizing GLCM, GRLM, and GLSZM texture methods and SVM-RBF classification algorithm. by Laurentius O. Osapoetra (9931759)

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. …”