Elapsed time of algorithms on benchmark functions. by Muhammad Zubair Rehman (11243478)

“…<p>Elapsed time of algorithms on benchmark functions.</p>…”

Genetic algorithm meta-parameters. by Larasmoyo Nugroho (18078260)

“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”

The entity relationship of DDPG algorithm. by Larasmoyo Nugroho (18078260)

“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”

Python cv coding screenshots of all developed fingerprints on distinct surfaces. by Nisha Yadav (366131)

Subjects:

a) DPR based Single Round MISTY1 / KASUMI, b) FI function. by Huang Jiexian (17060975)

The distribution function graphs of prediction errors for CLPREM model and its comparative models in three different environments, as well as the root mean square error of predicti... by Xiaorui Wu (8322705)

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

Subjects:

The comparison of results before and after using the preprocessing method is presented, including the distribution functions of the average prediction error in 10 runs under three... by Xiaorui Wu (8322705)

PATH has state-of-the-art performance versus previous binding affinity prediction algorithms. by Yuxi Long (11024307)

Subjects:

Diagram of the proposed solution algorithm. by Vytautas Abromavičius (22008573)

Comparative Analysis (Security Functionalities). by Naif Alzahrani (19992885)

Python-based Monte Carlo Simulation Tool by Yangfan Jiang (9372782)

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

Subjects:

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

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

Subjects:

Average function evaluation times of the three optimization algorithms. by Shuhui Yu (1535500)

“…<p>Average function evaluation times of the three optimization algorithms.…”

<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.…”

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

Subjects:

Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement by Antoine Falisse (6061601)

“…<div><p>Algorithmic differentiation (AD) is an alternative to finite differences (FD) for evaluating function derivatives. …”

Average CPU time (s) of all the referenced algorithm on benchmark function. by Aihua Guo (13267712)

“…<p>Average CPU time (s) of all the referenced algorithm on benchmark function.…”