Reward function related parameters. by Honglei Pang (22693724)

Subjects:

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. …”

A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finit... by Hassan Mehboob (8960273)

Knowledge graph model rating function. by Chunjuan Li (7890182)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by 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). …”

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

“…<p dir="ltr"><b>Opti2Phase: Python Scripts for Two-Stage Focal Reducer Design</b></p><p dir="ltr">The folder <b>Opti2Phase</b> contains the Python scripts used to generate the results presented in the manuscript. …”

Algorithm Parameter Setting. by Tong Zhou (3770)

“…This strategy uses the improved D3QN algorithm combined with the excellent smoothness of the sine function to evaluate driving safety, helping vehicles find suitable gaps in traffic flow. …”

Box plots of different algorithms on CEC2017 functions (dim = 30,100) and CEC2022 functions (dim = 20). by Qingwen Meng (156386)

Subjects:

A parabolic relationship between prediction errors and learning rates obtained by a cubic learning algorithm. by Boluwatife Ikwunne (22238697)

DE algorithm flow. by Ling Zhao (111365)

“…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …”

Test results of different algorithms. by Ling Zhao (111365)

“…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …”

Run times of two algorithms. by Gourab Saha (8987405)

Subjects:

Crop yield prediction accuracy using different ML algorithms. by Gourab Saha (8987405)

Subjects:

Parameters and variables used to generalized cost function. by Zhipeng Huang (1759759)

Subjects:

Performance of different algorithms across various regression metrics and datasets. by Shikun Chen (14625352)

Completion times for different algorithms. by Jianbin Zheng (587000)

“…Additionally, value function normalization and adaptive learning rate strategies are applied to accelerate convergence. …”

The average cumulative reward of algorithms. by Jianbin Zheng (587000)

“…Additionally, value function normalization and adaptive learning rate strategies are applied to accelerate convergence. …”

Pseudocode for the CORDIC algorithm to compute multiplication. by Mehdi Nadiri Andabili (22097275)

The difference between the end points of the objective function for different minimum requirement satisfaction rates. by Yuhang Wang (332111)

Pairwise comparisons and significance tests between algorithms for each regression metric. by Shikun Chen (14625352)