Process of choosing the optimal setting of algorithm parameters. by Katerina Barnova (11273670)

Table_1_A scheduling route planning algorithm based on the dynamic genetic algorithm with ant colony binary iterative optimization for unmanned aerial vehicle spraying in multiple tea fields.XLSX by Yangyang Liu (807797)

The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. by Olaide N. Oyelade (14047002)

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Datasets and their properties. by Olaide N. Oyelade (14047002)

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Parameter settings. by Olaide N. Oyelade (14047002)

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Algorithm factor level change curve. by Kuiyuan Pan (21145338)

Comparing ROSE and the NBI algorithms with varying sizes of the Pareto set/levels of recursion of the ROSE algorithm when applied to the BIOBJ problem: (a) 5 points/two recursion l... by Ihab Hashem (21156806)

Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”

Process of edge detection. by Haoqi Wu (8042648)

Pareto front representations obtained by solving the BIOBJ problem using the ROSE algorithm and the NBI algorithm, as well as a visualization of the solution process of the ROSE al... by Ihab Hashem (21156806)

Model selection by BO based on RCV(nv) from the simulated data with different noise levels. by László Zimányi (2649973)

Solving the three-objectives numerical problem from [36] using a generalized version of the ROSE algorithm for three-objective problems: (a) The Pareto front representation corresp... by Ihab Hashem (21156806)

BER at different SNR levels. by Hui Zhao (7395)

State-of-the-Art Skin Disease Classification Using Ensemble Learning and Advanced Image Processing by Nirupama (22148684)

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

“…The proposed approach contributes to inventory management by minimizing the negativities caused by demand variability through the Markov process. A mathematical model has been proposed for stock level optimization, but no feasible solution has been found. …”

Flowchart for the Tabu Search Algorithm [43]. by Ferhat Yuna (21519851)

“…The proposed approach contributes to inventory management by minimizing the negativities caused by demand variability through the Markov process. A mathematical model has been proposed for stock level optimization, but no feasible solution has been found. …”

Time Series Based Methods. by Ferhat Yuna (21519851)

“…The proposed approach contributes to inventory management by minimizing the negativities caused by demand variability through the Markov process. A mathematical model has been proposed for stock level optimization, but no feasible solution has been found. …”

Accuracy and average dots covered for difficulty level 11 using gradient descent to find the optimal solution. by Tarun Khajuria (12117309)

Genetic Algorithm (GA) and CAGE-based personalization block diagrams. by Dmitrii Smirnov (8822324)

“…<p>(<b>A</b>) Genetic algorithm schematic diagram. Initially a set of organisms is generated, each of which is determined by a random vector of scaling factors for optimized model parameters (step 1). …”

Adjusting the process. by Hui Yang (91136)