Load distribution versus number of time samples. by Nada Ahmed Ezz-Eldien (17396553)

“…This paper proposes an adaptive optimized vertical handover algorithm based on a multi-attribute decision-making (MADM) algorithm integrated with particle swarm optimization and gravitational search algorithm (PSOGSA) as a framework to implement the handover process. …”

Weights for voice application. by Nada Ahmed Ezz-Eldien (17396553)

“…This paper proposes an adaptive optimized vertical handover algorithm based on a multi-attribute decision-making (MADM) algorithm integrated with particle swarm optimization and gravitational search algorithm (PSOGSA) as a framework to implement the handover process. …”

Flowchart of weighting using the entropy method. by Nada Ahmed Ezz-Eldien (17396553)

“…This paper proposes an adaptive optimized vertical handover algorithm based on a multi-attribute decision-making (MADM) algorithm integrated with particle swarm optimization and gravitational search algorithm (PSOGSA) as a framework to implement the handover process. …”

Candidate networks selection percentages. by Nada Ahmed Ezz-Eldien (17396553)

“…This paper proposes an adaptive optimized vertical handover algorithm based on a multi-attribute decision-making (MADM) algorithm integrated with particle swarm optimization and gravitational search algorithm (PSOGSA) as a framework to implement the handover process. …”

Ping-Pong percentage results. by Nada Ahmed Ezz-Eldien (17396553)

“…This paper proposes an adaptive optimized vertical handover algorithm based on a multi-attribute decision-making (MADM) algorithm integrated with particle swarm optimization and gravitational search algorithm (PSOGSA) as a framework to implement the handover process. …”

Comparison of the performance of the emulators as a function of the size of the training set (resolution) for the agent-based cellular automata (CA) model of brain tumours. by Andreas Christ Sølvsten Jørgensen (13911723)

Ab Initio Modeling of MultiWall: A General Algorithm First Applied to Carbon Nanotubes by Naiara Leticia Marana (10720848)

“…A general, versatile and automated computational algorithm to design any type of multiwall nanotubes of any chiralities is presented for the first time. …”

Comparison of the performance of the emulators as a function of the size of the training set (resolution) for the agent-based cellular automata (CA) model of brain tumours. by Andreas Christ Sølvsten Jørgensen (13911723)

Mean number of stripes emerging from a group. by Pratik Mullick (12851011)

“trend+var” algorithm. by Roman Olson (6577004)

Test on the remeshing algorithm with <i>N</i> = 50 points. by Ondrej Maxian (8722185)

Data_Sheet_1_A multi-class logistic regression algorithm to reliably infer network connectivity from cell membrane potentials.PDF by Thierry Nieus (165355)

State Preparation in Quantum Algorithms for Fragment-Based Quantum Chemistry by Ruhee D’Cunha (8921372)

“…The localized active space–unitary coupled cluster (LAS–UCC) algorithm iteratively loads a fragment-based multireference wave function onto a quantum computer. …”

Accelerated MPC Algorithms and Augmented System Design for Legged Robots by John Ndegwa Nganga (21088838)

“…We make multiple advances to Differential Dynamic Programming (DDP), a classical control approach that solves for optimal trajectories based on a cost function and the robot's dynamics. …”

Various MFOs from three mechanisms. by Jingjing Ma (419752)

“…Hence, this paper introduces a novel enhanced MFO algorithm (BWEMFO) designed to improve algorithmic performance. …”

ROMK variants from the UK Biobank analyzed in this study. by Nga H. Nguyen (2075920)

Evaluation of the optimization algorithm using clinical microbiome reference values. by Juan Ricardo Velasco-Álvarez (16859181)

“…<p>A: Evolution of biomass fraction distribution for the cycles of adaptation enforced by the gradient descendant algorithm using a value of <i>α</i> = 0.125 and a microbiome composition from Mexican patients published by [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0290082#pone.0290082.ref020" target="_blank">20</a>]; B: Comparison of pie charts for the clinical reference biomass percentage distributions (left) and the obtained with the modeling strategy based on the gradient descent algorithm (right); C: Performance functional (<i>J</i>) evolution using clinical data from healthy Mexican patients for the simulation.…”

DataSheet_1_Identifying hub genes and common biological pathways between COVID-19 and benign prostatic hyperplasia by machine learning algorithms.docx by Hang Zhou (230977)

Characterization and Classification Using Autoregressive Modeling and Machine Learning Algorithms by Noushin R. Farnoud (4925308)

Out-of-sample accuracy vs. weighted <i>F</i>-score (comparison to ground-truth) for various clustering algorithms. by James Anibal (13899712)