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

Subjects:

Qualitative results for the F12 function. by Dingming Yang (8505990)

Subjects:

Qualitative results for the F14 function. by Dingming Yang (8505990)

Subjects:

Qualitative results for the F15 function. by Dingming Yang (8505990)

Subjects:

Qualitative results for the F13 function. by Dingming Yang (8505990)

Subjects:

Search algorithm performance comparison. by Zhaohui Du (414105)

The algorithm for the same-day surgery protocol. by Magnus Tveit (11442200)

Convergence curve of each DSM algorithms. by Manoj Kumar V. (18196645)

Subjects:

Hypothetical example illustrating how the <i>search</i>.<i>conv</i> function algorithm works. by Silvia Castiglione (5010581)

The optimal contact/quarantine rates from the family of functions (4) and (5) for Hainan and Xinjiang. by Mengqi He (5753525)

Subjects:

Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements by 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. …”

Parameters setting of function mining experiment. by Jin Ding (11522)

Subjects:

Optimization results of different algorithms. by Haijian Wang (746739)

“…<div><p>An Aquila optimizer-back propagation (AO-BP) neural network was used to establish an approximate model of the relationship between the design variables and the optimization objective to improve elevator block brake capabilities and achieve a lightweight brake design. Subsequently, the constraint conditions and objective functions were determined. …”

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

Parameters of the test function. by Yiqiong Gao (16698968)

“…The adaptive adjustment of the transition probability effectively balances the development and exploration abilities of the algorithm. The improved flower pollination algorithm (IFPA) outperformed six classical benchmark functions that were used to verify the superiority of the improved algorithm. …”

The optimal contact/quarantine rates from the family of functions (4) and (5) for Xi’an, Guangzhou and Yangzhou. by Mengqi He (5753525)

Subjects:

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

Subjects:

Parameter settings for metaheuristic algorithms. by Junhao Wei (6816803)

Subjects:

HIL test results of curved road: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sideslip angle; (f) Yaw rate. by Honglei Pang (22693724)

Subjects:

Unimodal benchmark functions. by Rahila Hafiz (18137254)

“…We propose a fusion of this algorithm with a discrete recombinant evolutionary strategy to enhance initialization diversity. …”