A gazelle optimization expedition for key term separated fractional nonlinear systems with application to electrically stimulated muscle modeling
Various real-time processes are effectively represented with a fractional nonlinear
autoregressive exogenous (F-NARX) model where estimation of model parameters is …
autoregressive exogenous (F-NARX) model where estimation of model parameters is …
Improved Jaya Synergistic Swarm Optimization Algorithm to Optimize Task Scheduling Problems in Cloud Computing
L Abualigah, AMA Hussein, MH Almomani… - … Informatics and Systems, 2024 - Elsevier
Cloud computing has emerged as a cornerstone technology for modern computational
paradigms due to its scalability and flexibility. One critical aspect of cloud computing is …
paradigms due to its scalability and flexibility. One critical aspect of cloud computing is …
[HTML][HTML] An unbiased method to partition diverse neuronal responses into functional ensembles reveals interpretable population dynamics during innate social …
In neuroscience, understanding how single-neuron firing contributes to distributed neural
ensembles is crucial. Traditional methods of analysis have been limited to descriptions of …
ensembles is crucial. Traditional methods of analysis have been limited to descriptions of …
Using Hybrid Mountain Gazelle Optimization and Particle Swarm Optimization Algorithms to Improve Clustering
E Mosavi, SAS Fazeli, E Abbasi, F Kaveh-yazdy - 2024 - researchsquare.com
Clustering plays a crucial role in data mining and machine learning, with the primary
objective being the identification of cohesive and distinct data groups, enabling the …
objective being the identification of cohesive and distinct data groups, enabling the …
Clustering and Classification for Dry Bean Feature Imbalanced Data
CY Lee, W Wang, JQ Huang - 2024 - researchsquare.com
The dry bean dataset of this study uses the imbalanced data set of the University of
California, Irvine (UCI) machine learning warehouse platform. The dataset consists of …
California, Irvine (UCI) machine learning warehouse platform. The dataset consists of …
[PDF][PDF] An Opposition-Based Learning-Based Search Mechanism for Flying Foxes Optimization Algorithm
C Zhang, L Liu, Y Yang, Y Sun, J Ning, Y Zhang… - cdn.techscience.cn
The flying foxes optimization (FFO) algorithm, as a newly introduced metaheuristic algorithm,
is inspired by the survival tactics of flying foxes in heat wave environments. FFO …
is inspired by the survival tactics of flying foxes in heat wave environments. FFO …