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. …"

Summary of literature review. 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. …"

Topic description. 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. …"

Notations along with their descriptions. 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. …"

Detail of the topics extracted from DUC2002. 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. …"

Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf حسب Muhammad Awais (263096)

"…Next, a hybrid feature extraction approach is presented leveraging transfer learning from selected deep neural network models, InceptionV3 and DenseNet201, to extract comprehensive feature sets. To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …"

Table_3_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.xlsx حسب Qian Wang (32718)

"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"

Image_1_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.jpeg حسب Qian Wang (32718)

"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"

Image_2_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.jpeg حسب Qian Wang (32718)

"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"

DataSheet_1_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.docx حسب Qian Wang (32718)

"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"

Image_3_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.jpeg حسب Qian Wang (32718)

"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"

Table_4_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.xlsx حسب Qian Wang (32718)

"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"

Table_2_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.xlsx حسب Qian Wang (32718)

"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"

Table_1_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.xlsx حسب Qian Wang (32718)

"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"