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. …”

The probability density function of points in feature space of variance versus mean of the local field for (0,3] and (0,3] displayed as a contour-plot. by Ali Talebi (7164203)

Four typical nonlinear transformation function curves. by Yuqi Xiong (12343771)

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-value on 23 benchmark functions (dim = 30). by Yuqi Xiong (12343771)

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23 benchmark functions. by Yu Liu (6938)

“…Engineering application results show that the improved CTCMKT algorithm can solve practical application problems.…”

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

“…The algorithm employs recurrent neural networks to capture and process historical information. …”

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

“…The algorithm employs recurrent neural networks to capture and process historical information. …”

Test results of different algorithms. 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. …”

Test function evolution curve. by Minan Tang (20389941)

Parameters of trained algorithms. by Swathi Anil (17382903)

Ranking distribution and average ranking on 23 benchmark functions. by Yuqi Xiong (12343771)

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Predictions from a Universal Value Function Approximator (UVFA) algorithm. by Sam Hall-McMaster (10343795)

WGCNA and machine learning algorithms. by Shushu Wang (6870191)

PATH has state-of-the-art performance versus previous binding affinity prediction algorithms. by Yuxi Long (11024307)

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Efficient Algorithms for GPU Accelerated Evaluation of the DFT Exchange-Correlation Functional by Ryan Stocks (16867476)

“…Two approaches, both leveraging batched dense linear algebra, are found to outperform the others across a suite of molecular benchmarks. We show that batched formation of the XC matrix from the density matrix yields the best performance for large (>O(103) basis functions), sparse systems such as glycine chains and water clusters. …”

ANOVA tests for Benchmark functions. by Yu Liu (6938)

“…Engineering application results show that the improved CTCMKT algorithm can solve practical application problems.…”

The Wilcoxon results for Benchmark functions. by Yu Liu (6938)

“…Engineering application results show that the improved CTCMKT algorithm can solve practical application problems.…”

Convergence graphs of Benchmark functions. by Yu Liu (6938)

“…Engineering application results show that the improved CTCMKT algorithm can solve practical application problems.…”

Localization error cumulative distribution function graph of EWKNN under different fingerprint databases. by Ruiyi Tang (10302578)

Results of the algorithms in solving engineering design optimization problems. by Yanzhao Gu (21192659)

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