<i>S</i>_<i>c</i> and rank of DSRABSQL and VDWOA algorithms in <i>G</i>_<i>1</i>. by Jin Zhang (53297)

<i>S</i>_<i>c</i> and rank of DSRABSQL and VDWOA algorithm in <i>G</i>_<i>2</i>. by Jin Zhang (53297)

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

“…<i>(b)</i> Metabolic byproducts move the relevant unperturbed state from <b>R</b>⁰ (gray ‘x’) to (black ‘x’), which is itself a function of the current environmental conditions. …”

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

Subjects:

The signal detection algorithm for constructing a neurometric function (the probability of segregation as a function of time) generates acceptable buildup fits at <i>DF</i> = 1, 3, 6, 9. by Quynh-Anh Nguyen (847240)

“…Lower panel: The signal detection algorithm constructs neurometric functions using numerical data from all <i>N</i>_<i>in</i> neuronal units. …”

-value on 23 benchmark functions (dim = 30). by Yuqi Xiong (12343771)

“…Experimental validation shows that on 23 benchmark functions and the CEC2022 test suite, MESBOA significantly outperforms the original Secretary Bird Optimization Algorithm (SBOA) and other comparative algorithms (such as GWO, WOA, PSO, etc.) in terms of convergence speed, solution accuracy, and stability. …”

Utility functions for attributes for different applications. by Nada Ahmed Ezz-Eldien (17396553)

Subjects: “…gravitational search algorithm…”

Sensitivity (<i>d</i>′) and criterion values as a function of prior identity decision (threshold = 0.5). by John J. Howard (9267903)

Python scripts used to model CPU errors by Poisson distribution density mass function and to draw graph of Poisson events (needs Matplot, SciPy, PysimpleGUI and NumPy) by Santhosh Kumar Rajamani (13023678)

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

“…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. …”

<i>min</i>, <i>avg</i>, <i>max</i> and <i>S</i>_<i>td</i> for rat575 obtained by three algorithms. by Jin Zhang (53297)

<i>min</i>, <i>avg</i>, <i>max</i> and <i>S</i>_<i>td</i> of ch150 obtained by three algorithms. by Jin Zhang (53297)

<i>min</i>, <i>avg</i>, <i>max</i> and <i>S</i>_<i>td</i> of fl1400 obtained by three algorithms. by Jin Zhang (53297)

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

Subjects:

The confusion matrix of the different algorithms. by Qiushi Wang (417314)

Summary statistics for the values of objective function—Phase I. by Fadi K. Dib (5204807)

The workflow used to analyze imbalanced and balanced sequences. by Solomon Shiferaw Beyene (9143178)

Performances of Naïve Bayes (NB), Multilayer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), Support Vector Machine (SVM) and K- Nearest Neighbors (KNN). by Solomon Shiferaw Beyene (9143178)

Accuracy, sensitivity, specificity and F-score. by Solomon Shiferaw Beyene (9143178)

The figures showed a comparison of the balanced and imbalanced sequences and performance of classifiers. by Solomon Shiferaw Beyene (9143178)