Two-dimensional (2-D) view of the benchmark functions. by Muhammad Zubair Rehman (11243478)

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Flowchart of CSCAHHO algorithm. by Yu-Jun Zhang (185411)

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Standard benchmark functions. by Yanzhao Gu (21192659)

“…The experimental results showed that GWOA achieved better convergence speed and solution accuracy than other algorithms in most test functions, especially in multimodal and compositional optimization problems, with an Overall Efficiency (OE) value of 74.46%. …”

Classification of meta-heuristic algorithms. by Yu-Jun Zhang (185411)

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Parameter settings for the comparative algorithms. by Yu-Jun Zhang (185411)

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Pseudo-code of CSCAHHO algorithm. by Yu-Jun Zhang (185411)

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Python-based Monte Carlo Simulation Tool by Yangfan Jiang (9372782)

Box plot of the algorithms based on 12 benchmark functions. by Chuang Zhang (2199421)

Convergence behavior of the algorithms based on 12 benchmark functions. by Chuang Zhang (2199421)

The decreasing pattern of Sine-Cosine indicating a switch from exploration to exploitation in the search space [71]. by Muhammad Zubair Rehman (11243478)

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Distribution of objective function values solved by three algorithms. by Meilin Zhu (688698)

Test results of the benchmark function (F1-F9, F19-F27), the dimension is fixed to 100. by Yu-Jun Zhang (185411)

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Test results of the benchmark function (F1-F9, F19-F27), the dimension is fixed to 60. by Yu-Jun Zhang (185411)

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Test results of the benchmark function (F1-F9, F19-F27), the dimension is fixed to 500. by Yu-Jun Zhang (185411)

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Algorithm comparison results of gear design problem. by Yu-Jun Zhang (185411)

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Modeling with uniform <i>σ</i> values. by Giacomo Janson (8138517)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

“…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”

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)