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. …”

RMSE values of different algorithms for different bands in the "Kherson" region. by YueSheng Jiang (19267984)

RMSE values of different algorithms for different bands in the "PY" region. by YueSheng Jiang (19267984)

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

Subjects:

Types of training algorithms. by Caixia Yan (6647072)

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

Parameters of the genetic algorithm. by Jian Ma (170138)

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

Subjects:

GenSearch algorithm. by Tarun Khajuria (12117309)

Subjects:

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

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. …”

Pseudo-code of DMDDPG algorithm. by Guohua Cao (697580)

“…First, we analyze the stages of hole-seeking, alignment, and insertion in the shaft-hole assembly process, based on a comprehensive study of the interactions between shafts and holes. Next, a reward function is designed by integrating the decoupled multi-agent deterministic deep deterministic policy gradient (DMDDPG) algorithm. …”

Reprojection of the validation points (9×6 lattice points) using the models obtained from the symbolic regression algorithm on the 6 calibration patterns. by Almoctar Hassoumi (6470354)

Crop yield prediction accuracy using different ML algorithms. by Gourab Saha (8987405)

Subjects:

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

Parameters of trained algorithms. by Swathi Anil (17382903)

An expectation-maximization algorithm for finding noninvadable stationary states. by Robert Marsland (8616483)

“…See main text and Appendix for model details and parameters. <i>(c)</i> Pseudocode for self-consistently computing <b>R</b>* and , which is identical to standard expectation-maximization algorithms employed for problems with latent variables in machine learning.…”

Continuous Probability Distributions generated by the PIPE Algorithm by LUIS G.B. PINHO (14073372)

“…<div><p>Abstract We investigate the use of the Probabilistic Incremental Programming Evolution (PIPE) algorithm as a tool to construct continuous cumulative distribution functions to model given data sets. …”

DE algorithm flow. 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. …”

Overview of the algorithm used to calculate Lyapunov exponents for assessing the stability and chaotic behavior of dynamical systems. by Adil Jhangeer (9711917)