On the benefits of using metaheuristics in the hyperparameter tuning of deep learning models for energy load forecasting
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 …
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
Developing 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 …
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
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 …
Things. This technology brings computing resources closer to the location where they are …
Metaheuristic-based hyperparameter tuning for recurrent deep learning: application to the prediction of solar energy generation
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 …
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
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 …
reveal the factors that shape the observed benzene levels and behavior under different …
[HTML][HTML] Novel hybrid firefly algorithm: An application to enhance XGBoost tuning for intrusion detection classification
The research proposed in this article presents a novel improved version of the widely
adopted firefly algorithm and its application for tuning and optimising XGBoost classifier …
adopted firefly algorithm and its application for tuning and optimising XGBoost classifier …
Software defects prediction by metaheuristics tuned extreme gradient boosting and analysis based on shapley additive explanations
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 …
making the difference between successful and failed projects. Although it is extremely …
Marine vessel classification and multivariate trajectories forecasting using metaheuristics-optimized extreme gradient boosting and recurrent neural networks
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 …
However, while these data are meticulously monitored and logged to maintain course, they …
Improving audit opinion prediction accuracy using metaheuristics-tuned XGBoost algorithm with interpretable results through SHAP value analysis
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 …
audits and surpass the benchmark set in a prior study from the literature. This tool could …
A novel firefly algorithm approach for efficient feature selection with COVID-19 dataset
Feature selection is one of the most important challenges in machine learning and data
science. This process is usually performed in the data preprocessing phase, where the data …
science. This process is usually performed in the data preprocessing phase, where the data …