Flowchart of proposed fitness function algorithm. by Ferhat Yuna (21519851)

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Standard benchmark functions used for the experimentation of EOSA and other similar optimization algorithms. by Tehnan I. A. Mohamed (16846175)

“…<p>Standard benchmark functions used for the experimentation of EOSA and other similar optimization algorithms.…”

Wilcoxon’s test results for EBJADE algorithms and other state-of-the-art CEA-ES algorithms using CEC2014 functions. by Yang Cao (53545)

“…<p>Wilcoxon’s test results for EBJADE algorithms and other state-of-the-art CEA-ES algorithms using CEC2014 functions.…”

Wilcoxon’s test results for EBJADE algorithms and other algorithms using CEC2014 functions for D = 30, 50 and 100. by Yang Cao (53545)

“…<p>Wilcoxon’s test results for EBJADE algorithms and other algorithms using CEC2014 functions for D = 30, 50 and 100.…”

Complementary cumulative distribution functions of in degree distribution and fitted power law, lognormal and truncated power law distributions. by Olga Valba (10531121)

Optimization Algorithm Applied to Environmental Control in Broiler Houses by MAC Benvenga (10447461)

“…The ideal rearing conditions were established as a goal, and we used the Simulated Annealing optimization algorithm to process the data. …”

Machine Learning Enhanced DFTB Method for Periodic Systems: Learning from Electronic Density of States by Wenbo Sun (531308)

“…Density functional tight binding (DFTB) is an approximate density functional based quantum chemical simulation method with low computational cost. …”

The results of ICA performed using PyNoetic. by Gursimran Singh (575288)

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MSE of MOP parameters with various schemes with <i>n</i> = 50 and <i>α</i> = 2, <i>θ</i> = 1.5, <i>β</i> = 0.5. by R. Alshenawy (13162866)

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MLE and Bayes point and interval estimate for real data sample. by R. Alshenawy (13162866)

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Point and interval prediction of the unobserved order statistics for scheme 3, with <i>α</i> = 0.5, <i>β</i> = 0.5, <i>θ</i> = 0.5. by R. Alshenawy (13162866)

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Point and interval prediction of the unobserved order statistics for scheme 2, with <i>α</i> = 0.5, <i>β</i> = 0.5, <i>θ</i> = 0.5. by R. Alshenawy (13162866)

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Point and interval prediction of the unobserved order statistics for scheme 1, with <i>α</i> = 0.5, <i>β</i> = 0.5, <i>θ</i> = 0.5. by R. Alshenawy (13162866)

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S1 Dataset - by R. Alshenawy (13162866)

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MSEs and biases for MLEs and bayes estimators of <i>α</i> = 2, <i>θ</i> = 1.5, <i>β</i> = 0.5. by R. Alshenawy (13162866)

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MSE of MOP parameters with various schemes with <i>n</i> = 50 and <i>α</i> = 2.5, <i>θ</i> = 1.5, <i>β</i> = 0.5. by R. Alshenawy (13162866)

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MSEs and biases for MLEs and bayes estimators of <i>α</i> = 2.5, <i>θ</i> = 1.5, <i>β</i> = 0.5. by R. Alshenawy (13162866)

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Data set of failure times of 20 mechanical components. by R. Alshenawy (13162866)

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Plot of the max K–S distance between two empirical CDF, and histogram of MOP distribution for data set. by R. Alshenawy (13162866)

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True and predicted observations under censoring scheme 1, 2, and 3. by R. Alshenawy (13162866)

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