Convergence speed of five algorithms. by 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. …”

The results of LASSO regression algorithm. by Xue Fu (549661)

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

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The benchmark functions. by Shuhui Yu (1535500)

Overview of different metaheuristic algorithms used in PV parameter estimation and their corresponding full names and acronyms. by Ziad M. Ali (12516532)

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Classification algorithm implemented in SPARTA. by Baptiste Ruiz (20285217)

The inversion results and curve of the objective function of the G-type geoelectric model. by Zhengyu Xu (8550660)

The inversion results and curve of the objective function of the AQ-type geoelectric model. by Zhengyu Xu (8550660)

The inversion results and curve of the objective function of the H-type geoelectric model. by Zhengyu Xu (8550660)

DE algorithm flow. by Ling Zhao (111365)

“…The model characterizes room functions and spatial locations through binary coding, and uses dynamic fitness function and backtracking strategy to improve space utilization and functional fitness. …”

The inversion results and curve of the objective function of AQ-type geoelectric model with noise. by Zhengyu Xu (8550660)

DMTD algorithm. by Yunhu Huang (21402795)

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Test function convergence curve. by Anqi Jiang (4583380)

“…Then, the upper-level model is solved using improved whale optimization, and the lower-level model is solved using improved Frank-Wolfe algorithm. The results showed that the accuracy and recall of the proposed improved whale optimization algorithm on the Iris dataset were 95.27% and 92.65%, respectively, which were superior to traditional whale optimization algorithm, moth flame optimization algorithm, moth flame optimization algorithm combined with chaos strategy, and adaptive firefly optimization algorithm. …”

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

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Percentage totBurden and percentage maxBurden reduced by UnitGreedy, SingletonGreedy, FastGreedy and baselines for = 0.535 in Iowa for FRED (first column) and SafeGraph (second col... by Jeffrey Keithley (14626551)

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The instance of MaxCasesAverted and MaxPeaksReduced is a graph <i>G</i> constructed from the given instance of Max k-SI. by Jeffrey Keithley (14626551)

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Percentage totBurden and percentage maxBurden reduced by UnitGreedy, FastGreedy and baselines for = 0.525 in Texas for FRED (first column) and SafeGraph (second column). by Jeffrey Keithley (14626551)

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Percentage totBurden and percentage maxBurden reduced by all approaches for = 0.5345 in New Hampshire for FRED (first column) and SafeGraph (second column). by Jeffrey Keithley (14626551)

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FastGreedy, UnitGreedy, SingletonGreedy, 3-EnumGreedy, and POMS comparison with respect to practical running time (estimated for POMS) to achieve approximation guarantee for New Ha... by Jeffrey Keithley (14626551)

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