Reward function related parameters. حسب Honglei Pang (22693724)

الموضوعات:

FAR-1: A Fast Integer Reduction Algorithm Compared to Collatz and Half-Collatz حسب Faizan Ali (21689861)

الموضوعات:

WGCNA and machine learning algorithms. حسب Shushu Wang (6870191)

Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements حسب Pascal Wang (10130612)

"…<div>This directory contains Python 3 scripts implementing the Trajectory Adaptive Multilevel Sampling algorithm (TAMS), a variant of Adaptive Multilevel Splitting (AMS), for the study of rare events. …"

Penalty functions used in different methods. حسب Souvik Seal (12437166)

Performance of ENQUIRE’s gene normalization algorithm. حسب Luca Musella (19986312)

Co-simulation architecture. حسب Honglei Pang (22693724)

الموضوعات:

Cost functions implemented in Neuroptimus. حسب Máté Mohácsi (20469514)

Listed python codes of our algorithm with explanations (Python 3.9 recommended). حسب Takayuki Niizato (162226)

Source code for DDQR and GeCo3 compression rate calculation. حسب Yujun Wang (1947196)

الموضوعات:

Source code for GeCo3 compression rate calculation using simulated data. حسب Yujun Wang (1947196)

الموضوعات:

Source code for GeCo3 compression rate calculation using real data. حسب Yujun Wang (1947196)

الموضوعات:

Comparison of compression rates of DDQR and Geco3 using simulated data around the region where the performance of DDQR exceeds that of GeCo3. حسب Yujun Wang (1947196)

الموضوعات:

Differences in computing performance between ENQUIRE’s gene normalization algorithm and GNorm2-Bioformer. حسب Luca Musella (19986312)

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

الموضوعات:

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

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

الموضوعات:

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

الموضوعات:

Development of the CO₂ Adsorption Model on Porous Adsorbent Materials Using Machine Learning Algorithms حسب Hossein Mashhadimoslem (11456548)

"…In this research study, we created a data set and collected data points from porous adsorbents (2789) from 21 published papers, including carbon-based, porous polymers, metal–organic frameworks (MOFs), and zeolites, to understand their characteristics for CO₂ adsorption. Different machine learning (ML) algorithms, such as NN, MLP-GWO, XGBoost, RF, DT, and SVM, have been applied to display the CO₂ adsorption performance as a function of characteristics and adsorption isotherm parameters. …"

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results حسب Se-Hee Jo (20554623)

"…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …"