a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset. by Nebojsa Bacanin (13932723)

MSE for ILSTM algorithm in binary classification. by Asmaa Ahmed Awad (16726315)

“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”

Proposed Algorithm. by Hend Bayoumi (22693738)

Optimization of tracking parameters based on <i>P</i>_<i>swap</i>. by Benjamin Gallois (10131683)

Homomorphic binary tree. by Jianhua He (341366)

Comparisons between ADAM and NADAM optimizers. by Hend Bayoumi (22693738)

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by 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. …”

Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF by Maya Khatun (7437011)

“…While generating the trial geometries, a Tabu list is used for storing the information of the already used trial geometries to avoid using the similar trial geometries. …”

Comparison between Bisection and Newton-Raphson in terms of (A) total time consumed, and (B) maximum computation rate. by Hend Bayoumi (22693738)

The flowchart of the proposed algorithm. by 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. …”

Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30. by Hend Bayoumi (22693738)

Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30. by Hend Bayoumi (22693738)

Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations. by Tristan Mary-Huard (3864)

Data_Sheet_1_Posiform planting: generating QUBO instances for benchmarking.pdf by Georg Hahn (12530469)

“…<p>We are interested in benchmarking both quantum annealing and classical algorithms for minimizing quadratic unconstrained binary optimization (QUBO) problems. …”

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

“…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”

Parameter settings. by Olaide N. Oyelade (14047002)

“…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”

Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. by Jiaqing Luo (10975030)

Performance Comparison of State-of-the-Art WPT-MEC Offloading Methods. by Hend Bayoumi (22693738)

CDF of task latency, approximated as the inverse of the achieved computation rate. by Hend Bayoumi (22693738)

The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames. by Hend Bayoumi (22693738)