Comparison of algorithms in two cases. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Flow of the NSGA-II algorithm. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

The optimal solution set of NYN by using different algorithms. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

The optimal solution set of HN by using different algorithms. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Results of proposed algorithms and algorithms in [9] for 18 instances. by Jin Zhang (53297)

Reward function related parameters. by Honglei Pang (22693724)

Subjects:

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

“…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…”

An expectation-maximization algorithm for finding noninvadable stationary states. by Robert Marsland (8616483)

“…<i>(c)</i> Pseudocode for self-consistently computing <b>R</b>* and , which is identical to standard expectation-maximization algorithms employed for problems with latent variables in machine learning.…”

Activation functions: Sigmoid function and ReLU function. by Wan-Hua Zhang (21601139)

APSO–CNN and FNN algorithms’ loss function training sets. by Ahmed Bahaa (12887063)

Subjects:

APSO–CNN and FNN algorithms’ loss function validation sets. by Ahmed Bahaa (12887063)

Subjects:

The APSO-CNN algorithm flowchart. by Ahmed Bahaa (12887063)

Subjects:

Route for bays29 output by ABSQL algorithm. by Jin Zhang (53297)

“…DSRABSQL builds upon the Q-learning (QL) algorithm. Considering its problems of slow convergence and low accuracy, four strategies within the QL framework are designed first: the weighting function-based reward matrix, the power function-based initial Q-table, a self-adaptive <i>ε-beam</i> search strategy, and a new Q-value update formula. …”

Simulation parameters for the QL, ABSQL and DSRABSQL algorithms. by Jin Zhang (53297)

Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

Subjects:

APSO–WOA–CNN and FNN algorithms’ loss function validation sets. by Ahmed Bahaa (12887063)

Subjects:

APSO–WOA–CNN and FNN algorithms’ loss function training sets. by Ahmed Bahaa (12887063)

Subjects:

Evaluation index performance among algorithms. by Ahmed Bahaa (12887063)

Subjects:

The APSO-WOA-CNN algorithm flowchart. by Ahmed Bahaa (12887063)

Subjects:

The optimal route of Berlin52 output by DSRABSQL algorithm. by Jin Zhang (53297)