Run times of two algorithms. by Gourab Saha (8987405)

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

Characterization and Classification Using Autoregressive Modeling and Machine Learning Algorithms by Noushin R. Farnoud (4925308)

Machine learning algorithm parameters. by Namal Rathnayake (15361124)

“…Correlation of coefficient (R), Per cent-Bias (bias), Nash Sutcliffe Model efficiency (NSE), Mean Absolute Relative Error (MARE), Kling-Gupta Efficiency (KGE), and Root mean square error (RMSE) were used as the comparative indices between Gradient Boosting Algorithms and Adaptive Network-based Fuzzy Inference Systems. …”

Pseudocode for the CORDIC algorithm to compute multiplication. by Mehdi Nadiri Andabili (22097275)

Comparison of algorithm search curves. by Bowen Li (200859)

“…Then, combining with the idea of fast density clustering algorithm, the number of hidden layer neurons of RBF is determined by finding the point with the highest density and using it as the hidden layer neuron. …”

Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

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Example of the CNF function for off-axis DHM holograms recorded in a non-telecentric configuration. by Raul Castañeda (13932971)

WERs for different SE algorithms. by Fahad Khalil Peracha (15453204)

Running memory of the algorithms. by Yanju Zhang (437336)

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The final population of the optimization algorithm based on the two goals of accuracy and diversity. by Kaveh Faraji Googerdchi (18778727)

The structure of genetic algorithm (GA). by Ali Akbar Moosavi (17769033)

“…First, physico-chemical inputs as bulk density (BD), initial water content (W_i), saturated water content (W_s), mean weight diameter (MWD), and geometric mean diameter (GMD) of aggregates, pH, electrical conductivity (EC), and calcium carbonate equivalent (CCE) were measured. Then, radial basis functions (RBFNNs), multilayer perceptron (MLPNNs), hybrid genetic algorithm (GA-NNs), and particle swarm optimization (PSO-NNs) neural networks were utilized to develop PTFs and compared their accuracy with the traditional regression model (MLR) using statistical indices. …”

Flowchart for the Tabu Search Algorithm [43]. by Ferhat Yuna (21519851)

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Line charts of the elbow method and the k-value selection algorithm: (A) elbow method; (B) k-value selection algorithm. by Jingnan Yan (20727331)

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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.…”

Genetic algorithm flowchart. by Junjie He (700642)

Subjects: “…coverage attenuation function…”

GenSearch algorithm. by Tarun Khajuria (12117309)

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Visualization of the RITSS algorithm. by Julian Hecker (758791)

Features selection using the GA model. by Tuan Anh Pham (1346049)

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Gillespie algorithm simulation parameters. by Nicholas H. Vitale (20469289)

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