Networking Chemicals Flows: Efficiency–Value–Environment Functionalized Symbiosis Algorithms and Application by Yizheng Lyu (17346506)

Slicing aided hyper inference algorithm. by Chunhua Yang (346871)

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Example psychometric functions for observer DHB. by Daniel H. Baker (11559693)

Classical benchmark functions [39]. by Junhao Wei (6816803)

“…We also conducted a quantitative analysis of RWOA and compared its performance with other state-of-the-art (SOTA) metaheuristic algorithms. …”

Results on the comparison of evolutionary and greedy algorithms with exact solution. by Alexander Andreev (16822333)

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Contrast enhancement of digital images using dragonfly algorithm by Soumyajit Saha (19726163)

“…Comparisons with state-of-art methods ensure the superiority of the proposed algorithm. The Python implementation of the proposed approach is available in this <a href="https://github.com/somnath796/DA_contrast_enhancement" target="_blank">Github repository</a>.…”

WSN optimized by different algorithms. by Qingwen Meng (156386)

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Compare algorithm parameter settings. by Qingwen Meng (156386)

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Distribution of small airway disease index (SADI in degree angle) in pulmonary function tests with FEV1/FVC ≥ 0.7. by Yuh-Chin T. Huang (17867207)

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Matlab code of a function used in S2 File. by Hiroko Kato Solvang (5718250)

Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. by Francisco Páscoa dos Santos (16510676)

“…<p>A) Resulting cluster inertia from applying the k-means algorithm described in the methods to empirical averaged functional connectivity from healthy subjects, with different numbers of clusters. …”

Mean training time of different algorithms. by 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.…”

Algorithm ranking under different dimensions. by 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.…”

Results on solving TSS using different evolutionary and greedy algorithms. by Alexander Andreev (16822333)

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S1 Data - by Dingming Yang (8505990)

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Flowchart of P&O-based MPPT algorithm. by Luqman Khan (17921419)

Flowchart of system algorithm. by Syed Zahurul Islam (9635163)

The repair algorithm restores the electrophysiological behaviour of cut and repaired mouse pyramidal cells and allows for better predictions of neuronal function in human neurons. by Moritz Groden (18018276)

The empirical distribution function and fitted distribution functions for data sets <i>Q</i> and <i>T</i>. by Salem A. Alyami (10572611)

Tuned parameters of algorithms. by Kaveh Faraji Googerdchi (18778727)