Function graph and algorithm iterative graph. حسب WanRu Zhao (18980374)

الموضوعات:

Our algorithms process large data sets within a minute. حسب Manu Aggarwal (15990691)

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

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer حسب 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.…"

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

Illustration of methods based on Green’s function first-passage algorithms. حسب Jean Marc Tregan (15195173)

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

الموضوعات:

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

الموضوعات:

Optimization results of test functions for different algorithm improvement points. حسب WanRu Zhao (18980374)

الموضوعات:

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

الموضوعات:

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

الموضوعات:

ANOVA test over the seven benchmark functions, treatment is between columns and residual is within columns. حسب El-Sayed M. El-kenawy (14581088)

Reward function related parameters. حسب Honglei Pang (22693724)

الموضوعات:

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

الموضوعات:

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

الموضوعات:

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

Networking Chemicals Flows: Efficiency–Value–Environment Functionalized Symbiosis Algorithms and Application حسب Yizheng Lyu (17346506)

Networking Chemicals Flows: Efficiency–Value–Environment Functionalized Symbiosis Algorithms and Application حسب Yizheng Lyu (17346506)

Networking Chemicals Flows: Efficiency–Value–Environment Functionalized Symbiosis Algorithms and Application حسب Yizheng Lyu (17346506)