Specific information on the 7 benchmark functions. حسب M. A. JiMing (19207527)

Comparison of results of different algorithms. حسب Zhibo Fu (19009854)

الموضوعات:

Standard benchmark functions. حسب Yanzhao Gu (21192659)

الموضوعات:

Loss function as a function of a number of iterations. حسب Kiyoshiro Okada (10711332)

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

الموضوعات:

The benchmark functions. حسب Shuhui Yu (1535500)

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. …"

Compare algorithm parameter settings. حسب Yuqi Xiong (12343771)

الموضوعات:

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

"…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"

Boxplot of fitness in various algorithms. حسب Wei Liu (20030)

"…The convergence of SGWO was analyzed by mathematical theory, and the optimization ability of SGWO and the prediction performance of SGWO-Elman were examined using comparative experiments. The results show: (1) the global convergence probability of SGWO was 1, and its process was a finite homogeneous Markov chain with an absorption state; (2) SGWO not only has better optimization performance when solving complex functions of different dimensions, but also when applied to Elman for parameter optimization, SGWO can significantly optimize the network structure and SGWO-Elman has accurate prediction performance.…"

Function convergence curve. حسب Guilin Yang (583364)

"…To evaluate the performance of the proposed algorithm, 27 well-known test reference functions were selected for experimentation, which showed significant advantages compared to other algorithms. …"

Membership function of each target. حسب Tianrui Zhang (2294542)

الموضوعات:

Comparison of softsign function and tanh function. حسب Peihan Wen (6324315)

الموضوعات:

23 benchmark functions. حسب Yu Liu (6938)

"…<div><p>The competition of tribes and cooperation of members algorithm (CTCM) is a novel swarm intelligence algorithm, which increases the diversity of the population to a certain extent through tribal competition and member cooperation mechanisms. …"

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

الموضوعات:

Ave and Std of different algorithms. حسب Yanzhao Gu (21192659)

الموضوعات:

Parameter settings for metaheuristic algorithm. حسب Yanzhao Gu (21192659)

الموضوعات:

Path planning flowchart for improving A* and DWA fusion algorithms. حسب Peiying Li (797714)

الموضوعات:

Traditional A* and research algorithm planned paths perform successfully. حسب Peiying Li (797714)

الموضوعات:

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

"…In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …"