Algorithm detection steps. by José M. Rivera-Arbeláez (12418512)

Algorithm of the brightness scale calibration experiment. by Krzysztof Petelczyc (3954203)

“…<p>In the algorithm, the following variables were used: “I” denotes the current luminous intensity of the reference diode, “inc” denotes the current difference between reference and target diode luminous intensity; “cnt” is the current number of performed trials, while “correct” is a counter of correct answers in cnt trials, both of them are counted separately for every settings of I and inc. …”

Statistical results of various algorithms. by ZeSheng Lin (20501356)

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Images of partial benchmark functions. by ZeSheng Lin (20501356)

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Execution Steps of the EOF Algorithm. by Zezhi Lin (22521663)

Predictive Mixing for Density Functional Theory (and Other Fixed-Point Problems) by L. D. Marks (1949689)

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If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

“…Each algorithm return a set of coarsened <i>variables</i> (a grouping of species into three groups) and a <i>model</i> that uses these variables to predict the function. …”

Procedure of the DCT-based EIT algorithm. by Rongqing Chen (249906)

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Automatic cropping algorithm. by Thomas W Georgi (12427189)

Curve of step response signal of 6 algorithms. 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. …”

The number of inactive nodes as a function of time steps in (a) a random network and (b) a scale-free network. by Waseem Al-Aqqad (14123917)

The number of inactive nodes as a function of time steps at higher values of <i>P</i> and <i>α</i> in (a) a random network and (b) a scale-free network. by Waseem Al-Aqqad (14123917)

Algorithm diagnostic accuracy comparison chart. by Bowen Li (200859)

Convergence of the Cut Value of QFMA as a function of steps for the G1 problem. by Máté Tibor Veszeli (12160786)

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Limitation of the conventional DBT reconstruction algorithm. by Yunsu Choi (11993484)

<b>Algorithm Pseudocode</b> by Yibin Zhao (22425801)

Representative neurons and their corresponding step functions. by Reem Khalil (10898163)

Comparison of softsign function and tanh function. by Peihan Wen (6324315)

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Test of polymethyl methacrylate (C₅O₂H₈) through algorithm: Curves of both objective function and fractional weight in the process of identifying third chemical constituent after H was assumed, i.e., step 2 in Figure 2. by Dong Hyeok Choi (12562048)

Comparison of step size 0.1 with the actual energy consumption step count. by Zhiqun Lin (1429501)

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