The benchmark test functions. حسب Xuxu Zhong (10099054)

الموضوعات:

The optimization result of 10 benchmark functions for different algorithms (D = 10). حسب Yu Li (183836)

The optimization result of 10 benchmark functions for different algorithms (D = 30). حسب Yu Li (183836)

The result of CEC2010 standard functions for different algorithms (D = 30). حسب Yu Li (183836)

The optimization result of 10 benchmark functions for different algorithms (D = 100). حسب Yu Li (183836)

The convergence curves of the function in different dimensions. حسب Yu Li (183836)

Satisfaction of university teachers and students with various face recognition algorithms. حسب Yan Liu (25061)

The block diagram of the ASO algorithm implementation for inverse modeling. حسب Ahmad Al-Talabi (21387479)

The parameters of the algorithms. حسب Yu Li (183836)

Details of the metaheuristic algorithms. حسب Yanzhao Gu (21192659)

الموضوعات:

Algorithm of genetic workup. حسب Idoia Martinez de Lapiscina (16528261)

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The pseudocode for the NAFPSO algorithm. حسب Huichao Guo (14515171)

"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"

PSO algorithm flowchart. حسب Huichao Guo (14515171)

"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"

Comparison results of dynamic shift functions. حسب Yong Gao (29929)

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Search Algorithms and Loss Functions for Bayesian Clustering حسب David B. Dahl (11761055)

"…<p>We propose a randomized greedy search algorithm to find a point estimate for a random partition based on a loss function and posterior Monte Carlo samples. …"

Benchmark test function result. حسب HaoCheng Wang (6089567)

Fixed multimodal test functions. حسب HaoCheng Wang (6089567)

Main parameters of the 7 algorithms. حسب Xuan Chen (158617)

الموضوعات:

Results of searching performance of different algorithm models on the Rosenbrock function, Ackley function, and Rastrigin function. حسب Rui Zhang (13940)

Comparison of location privacy protection algorithms. حسب Li He (134049)