On the benefits of using metaheuristics in the hyperparameter tuning of deep learning models for energy load forecasting

N Bacanin, C Stoean, M Zivkovic, M Rakic… - Energies, 2023 - mdpi.com
An effective energy oversight represents a major concern throughout the world, and the
problem has become even more stringent recently. The prediction of energy load and …

Hybrid CNN and XGBoost model tuned by modified arithmetic optimization algorithm for COVID-19 early diagnostics from X-ray images

M Zivkovic, N Bacanin, M Antonijevic, B Nikolic… - Electronics, 2022 - mdpi.com
Develo** countries have had numerous obstacles in diagnosing the COVID-19 worldwide
pandemic since its emergence. One of the most important ways to control the spread of this …

Modified firefly algorithm for workflow scheduling in cloud-edge environment

N Bacanin, M Zivkovic, T Bezdan… - Neural computing and …, 2022 - Springer
Edge computing is a novel technology, which is closely related to the concept of Internet of
Things. This technology brings computing resources closer to the location where they are …

Hybridized sine cosine algorithm with convolutional neural networks dropout regularization application

N Bacanin, M Zivkovic, F Al-Turjman… - Scientific Reports, 2022 - nature.com
Deep learning has recently been utilized with great success in a large number of diverse
application domains, such as visual and face recognition, natural language processing …

Performance of a novel chaotic firefly algorithm with enhanced exploration for tackling global optimization problems: Application for dropout regularization

N Bacanin, R Stoean, M Zivkovic, A Petrovic… - Mathematics, 2021 - mdpi.com
Swarm intelligence techniques have been created to respond to theoretical and practical
global optimization problems. This paper puts forward an enhanced version of the firefly …

Multi-objective task scheduling in cloud computing environment by hybridized bat algorithm

T Bezdan, M Zivkovic, N Bacanin… - Journal of Intelligent …, 2022 - content.iospress.com
Cloud computing represents relatively new paradigm of utilizing remote computing
resources and is becoming increasingly important and popular technology, that supports on …

Multi-objective grey wolf optimizer algorithm for task scheduling in cloud-fog computing

FA Saif, R Latip, ZM Hanapi, K Shafinah - IEEE Access, 2023 - ieeexplore.ieee.org
The revolution of IoT and its capabilities to serve various fields led to generating a large
amount of data for processing. Tasks that require an instant response, especially with …

Novel improved salp swarm algorithm: An application for feature selection

M Zivkovic, C Stoean, A Chhabra, N Budimirovic… - Sensors, 2022 - mdpi.com
We live in a period when smart devices gather a large amount of data from a variety of
sensors and it is often the case that decisions are taken based on them in a more or less …

A review of task scheduling in cloud computing based on nature-inspired optimization algorithm

FS Prity, MH Gazi, KMA Uddin - Cluster computing, 2023 - Springer
The advent of the cloud computing paradigm allowed multiple organizations to move,
compute, and host their applications in the cloud environment, enabling seamless access to …

Hybrid fruit-fly optimization algorithm with k-means for text document clustering

T Bezdan, C Stoean, AA Naamany, N Bacanin… - Mathematics, 2021 - mdpi.com
The fast-growing Internet results in massive amounts of text data. Due to the large volume of
the unstructured format of text data, extracting relevant information and its analysis becomes …