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)

Optimizer power output response against six non-convex machines. by Ijaz Ahmed (1545961)

Optimizer power output response against forty non-convex machines. by Ijaz Ahmed (1545961)

Optimizer power output response against thirteen non-convex machines. by Ijaz Ahmed (1545961)

Optimizer fitness level response against six non-convex machines. by Ijaz Ahmed (1545961)

Optimizer fitness level response against forty non-convex machines. by Ijaz Ahmed (1545961)

Optimizer fitness level response against thirteen non-convex machines. by Ijaz Ahmed (1545961)

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

Subjects:

Comparative analysis of algorithms. by Xumin Zhao (18261643)

“…Notably, the LIRU algorithm registers a 5% increment in one-hop hit ratio relative to the LFU algorithm, a 66% enhancement over the LRU algorithm, and a 14% elevation in system hit ratio against the LRU algorithm. …”

Predicted power spectral density of fluorescence under the influence of molecular binding kinetics for system with 1 nM and 100 nM of ssDNA against temperature. by Nicholas H. Vitale (20469289)

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... by Hector Torres (11708207)

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

Subjects:

Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

Function testing and iterative variation diagram. by Yun Qi (560401)

Cryptographic hash function. by Evans Osei Kofi (15285194)

Evolution of objective function. by Serdar Ekinci (15927455)

“…Comparative assessments against existing optimization algorithms and recent techniques confirm QWGBO’s superior performance. …”

Flowchart of improved FOX optimization algorithm. by Mahmood A. Jumaah (22272371)

“…Additionally, it achieved 880 wins, 228 ties, and 348 losses against 16 optimization algorithms across all involved functions and problems. …”