Multi-functional liquid crystal devices based on random binary matrix algorithm by Tibin Zeng (10890697)

“…<p>Multi-functional diffraction gratings have found broad applications in laser processing, medicine, beam manipulation, etc. …”

A parabolic relationship between prediction errors and learning rates obtained by a cubic learning algorithm. by Boluwatife Ikwunne (22238697)

Curves of sigmoid functions used in our proposed algorithm. by Binh Thanh Dang (12368831)

“…<p>Curves of sigmoid functions used in our proposed algorithm.</p>…”

MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

Results of the PSO-Kmeans-ANMS algorithm for the Rastrigin function. by Rutinaldo Aguiar Nascimento (14259594)

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Results of the PSO-Kmeans-ANMS algorithm for the Rosenbrock function. by Rutinaldo Aguiar Nascimento (14259594)

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The parameters of algorithms. by Le Huu Binh (18340233)

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Convergence curves of the IMGO algorithm and comparison algorithms on functions <i>f</i>14−<i>f</i>23. by Ying Li (38224)

“…<p>Convergence curves of the IMGO algorithm and comparison algorithms on functions <i>f</i>14−<i>f</i>23.…”

Convergence curves of the IMGO algorithm and comparison algorithms on functions <i>f</i>8−<i>f</i>13. by Ying Li (38224)

“…<p>Convergence curves of the IMGO algorithm and comparison algorithms on functions <i>f</i>8−<i>f</i>13.…”

Algorithm implemented using SQL with fulltext search feature. by Kathleen M. Akgün (3697702)

Standard benchmark functions used for the experimentation of EOSA and other similar optimization algorithms. by Tehnan I. A. Mohamed (16846175)

“…<p>Standard benchmark functions used for the experimentation of EOSA and other similar optimization algorithms.…”

Critical values of membership functions learned from the study cohort by the algorithm. by Yufeng Zhang (195768)

Eight commonly used benchmark functions. by Guangwei Liu (181992)

“…Secondly, the nonlinear convergence factor is constructed to replace the original random factor <i>c</i>₁ to coordinate the algorithm’s local exploitation and global exploration performance, which effectively improves the ability of the algorithm to escape extreme values and fast convergence. …”

Distribution of DLCO in pulmonary function tests with discrepant interpretations between the algorithm and the clinicians. by Yuh-Chin T. Huang (17867207)

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Search Algorithms and Loss Functions for Bayesian Clustering by 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. …”

Objective functions (i.e., RMSEs) and time of optimization for different population sizes of the used algorithms. by Yao Peng (1928524)

“…<p>Objective functions (i.e., RMSEs) and time of optimization for different population sizes of the used algorithms.…”

Convergence of the numerical solution of the non-linear equation system through the iterations <i>p</i> using the Newton-Raphson algorithm and the Levenberg–Marquardt algorithm. by Martin Dodek (20623832)

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