Data sample for the total number of airline passengers at six airports (general directorate of state airports authority, 2019), approximate-area measurements, and average number of... حسب Emre Demir (6190242)

Failure Samples and Fitting Results. حسب Dongyan Wang (195482)

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. …"

Deterministic-optimal policy in the EGT-model. حسب MingYi Wang (2807581)

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. …"

Plots of steady-state frequency control. حسب Salisu Mohammed (772274)

"…The optimization problem was formulated based on the network power flow and the discrete-time sampling of the constrained control parameters. …"

Plots of steady-state voltage control. حسب Salisu Mohammed (772274)

"…The optimization problem was formulated based on the network power flow and the discrete-time sampling of the constrained control parameters. …"

Plots of steady-state input trajectory. حسب Salisu Mohammed (772274)

"…The optimization problem was formulated based on the network power flow and the discrete-time sampling of the constrained control parameters. …"

Two-dimensional benchmark test-functions. حسب Salisu Mohammed (772274)

"…The optimization problem was formulated based on the network power flow and the discrete-time sampling of the constrained control parameters. …"

Block diagram of autonomous microgrid. حسب Salisu Mohammed (772274)

"…The optimization problem was formulated based on the network power flow and the discrete-time sampling of the constrained control parameters. …"

Thirty-dimensional benchmark test-functions. حسب Salisu Mohammed (772274)

"…The optimization problem was formulated based on the network power flow and the discrete-time sampling of the constrained control parameters. …"

Performance of algorithms outside the training species. حسب Sven B. Gould (12237287)

Iteration diagram of genetic algorithm. حسب Ke Peng (2220973)

"…The results show that: (1) The applied SMOTEENN is more effective than SMOTE and ADASYN in dealing with the imbalance of banking data. (2) The F1 and AUC values of the model improved and optimized by XGBoost using genetic algorithm can reach 90% and 99%, respectively, which are optimal compared to other six machine learning models. …"

Genetic algorithm flow chart. حسب Ke Peng (2220973)

"…The results show that: (1) The applied SMOTEENN is more effective than SMOTE and ADASYN in dealing with the imbalance of banking data. (2) The F1 and AUC values of the model improved and optimized by XGBoost using genetic algorithm can reach 90% and 99%, respectively, which are optimal compared to other six machine learning models. …"

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. …"

Sample of train service network. حسب Jiren CAO (20442214)

Results of genetic algorithm tuning parameters. حسب Ke Peng (2220973)

"…The results show that: (1) The applied SMOTEENN is more effective than SMOTE and ADASYN in dealing with the imbalance of banking data. (2) The F1 and AUC values of the model improved and optimized by XGBoost using genetic algorithm can reach 90% and 99%, respectively, which are optimal compared to other six machine learning models. …"

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. …"

Importance ranking and 10-fold cross-validation of the analyzed variables using a random forest model to determine the optimal number of variables. حسب Xin Luo (428648)