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 …

Software defects prediction by metaheuristics tuned extreme gradient boosting and analysis based on shapley additive explanations

T Zivkovic, B Nikolic, V Simic, D Pamucar… - Applied Soft …, 2023 - Elsevier
Software testing represents a crucial component of software development, and it is usually
making the difference between successful and failed projects. Although it is extremely …

Tuning attention based long-short term memory neural networks for Parkinson's disease detection using modified metaheuristics

A Cuk, T Bezdan, L Jovanovic, M Antonijevic… - Scientific Reports, 2024 - nature.com
Parkinson's disease (PD) is a progressively debilitating neurodegenerative disorder that
primarily affects the dopaminergic system in the basal ganglia, impacting millions of …

Metaheuristic-based hyperparameter tuning for recurrent deep learning: application to the prediction of solar energy generation

C Stoean, M Zivkovic, A Bozovic, N Bacanin… - Axioms, 2023 - mdpi.com
As solar energy generation has become more and more important for the economies of
numerous countries in the last couple of decades, it is highly important to build accurate …

The explainable potential of coupling metaheuristics-optimized-xgboost and shap in revealing vocs' environmental fate

L Jovanovic, G Jovanovic, M Perisic, F Alimpic… - Atmosphere, 2023 - mdpi.com
In this paper, we explore the computational capabilities of advanced modeling tools to
reveal the factors that shape the observed benzene levels and behavior under different …

Optimizing long-short-term memory models via metaheuristics for decomposition aided wind energy generation forecasting

M Pavlov-Kagadejev, L Jovanovic, N Bacanin… - Artificial Intelligence …, 2024 - Springer
Power supply from renewable energy is an important part of modern power grids. Robust
methods for predicting production are required to balance production and demand to avoid …

[HTML][HTML] Forecasting bitcoin: Decomposition aided long short-term memory based time series modeling and its explanation with Shapley values

V Mizdrakovic, M Kljajic, M Zivkovic, N Bacanin… - Knowledge-Based …, 2024 - Elsevier
Bitcoin price volatility fascinates both researchers and investors, studying features that
influence its movement. This paper expends on previous research and examines time series …

Improving audit opinion prediction accuracy using metaheuristics-tuned XGBoost algorithm with interpretable results through SHAP value analysis

M Todorovic, N Stanisic, M Zivkovic, N Bacanin… - Applied Soft …, 2023 - Elsevier
This study aims to create a machine learning model that can predict opinions in external
audits and surpass the benchmark set in a prior study from the literature. This tool could …

[HTML][HTML] Marine vessel classification and multivariate trajectories forecasting using metaheuristics-optimized extreme gradient boosting and recurrent neural networks

A Petrovic, R Damaševičius, L Jovanovic, A Toskovic… - Applied Sciences, 2023 - mdpi.com
Maritime vessels provide a wealth of data concerning location, trajectories, and speed.
However, while these data are meticulously monitored and logged to maintain course, they …

Detecting Parkinson's disease from shoe-mounted accelerometer sensors using convolutional neural networks optimized with modified metaheuristics

L Jovanovic, R Damaševičius, R Matic, M Kabiljo… - PeerJ Computer …, 2024 - peerj.com
Neurodegenerative conditions significantly impact patient quality of life. Many conditions do
not have a cure, but with appropriate and timely treatment the advance of the disease could …