Iterative optimization convergence curve of each algorithm. حسب Guangwei Liu (181992)

The optimization results of each algorithm for the 8 benchmark functions. حسب Guangwei Liu (181992)

Optimal results of the different algorithms on the speed design reducer problem. حسب Guangwei Liu (181992)

Optimal results of the different algorithms on the pressure vessel design problem. حسب Guangwei Liu (181992)

Optimal results of the different algorithms on the gear train design problem. حسب Guangwei Liu (181992)

The optimization results of each algorithm for the CEC2019 benchmark functions. حسب Guangwei Liu (181992)

Optimal results of the different algorithms on the tension/compression spring design problem. حسب Guangwei Liu (181992)

Generator loss of the proposed method. حسب Nanavath Kiran Singh Nayak (22184565)

"…Initially, Four-Q curve authentication is performed, followed by univariate ensemble feature selection to select optimal switches. Then, the data collected through the switches are classified as normal, assault, and suspect packets based on the Dual Discriminator Conditional Generative Adversarial Network (DDcGAN) approach. …"

Pseudocode of artificial dragonfly algorithm. حسب Ghassan Ahmed Ali (17041488)

"…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"

DataSheet1_Optimal capacity configuration of the wind-storage combined frequency regulation system considering secondary frequency drop.docx حسب Dongdong Li (123985)

The Hopfield artificial neural network algorithm. حسب Ghassan Ahmed Ali (17041488)

"…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm حسب Hussein Ali Bardan (21976208)

"…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …"

Algorithm for generating hyperparameter. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"

Machine learning deployment strategies and schematic illustration of the proposed generative adversarial algorithm for domain adaptation. حسب Aly A. Valliani (13251484)

"…<b>(C)</b> Schematic of the proposed algorithm. a) Real data from a source domain is translated by the generator to resemble data from a specified target domain while maintaining underlying semantic qualities of the input image. b) Translated data is reconstructed by the generator to resemble data from the source domain to maintain domain-agnostic image characteristics with a semantic consistency constraint ensuring that reconstructed images maintain the semantic characteristics of the source data. c) The discriminator aims to distinguish between real and synthetic images and identify the domain of input images to constrain the generator to produce realistic-looking synthetic images from a specified domain. d) A target discriminator is fine-tuned on synthetic images to better identify opacity in the target domain.…"

Results of machine learning algorithm. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"

ROC comparison of machine learning algorithm. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"

The flowchart of the proposed algorithm. حسب Muhammad Ayyaz Sheikh (18610943)

"…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"

S1 Data - حسب Guangwei Liu (181992)

"…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …"

Curve of step response signal of 6 algorithms. حسب Guangwei Liu (181992)

"…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …"

Best optimizer results of Lightbgm. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"