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 …
Multi-input CNN based vibro-acoustic fusion for accurate fault diagnosis of induction motor
Induction motor (IM) is a highly efficient prime mover in industrial applications. To maintain
an uninterrupted operation, accurate fault diagnosis system of IM is required. It can help to …
an uninterrupted operation, accurate fault diagnosis system of IM is required. It can help to …
Mapping roofing with asbestos-containing material by using remote sensing imagery and machine learning-based image classification: A state-of-the-art review
Building roofing produced with asbestos-containing materials is a significant concern due to
its detrimental health hazard implications. Efficiently locating asbestos roofing is essential to …
its detrimental health hazard implications. Efficiently locating asbestos roofing is essential to …
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 …
Application of natural language processing and machine learning boosted with swarm intelligence for spam email filtering
Spam represents a genuine irritation for email users, since it often disturbs them during their
work or free time. Machine learning approaches are commonly utilized as the engine of …
work or free time. Machine learning approaches are commonly utilized as the engine of …
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 …
Augmented weighted K-means grey wolf optimizer: An enhanced metaheuristic algorithm for data clustering problems
This study presents the K-means clustering-based grey wolf optimizer, a new algorithm
intended to improve the optimization capabilities of the conventional grey wolf optimizer in …
intended to improve the optimization capabilities of the conventional grey wolf optimizer in …
Machine learning tuning by diversity oriented firefly metaheuristics for industry 4.0
Abstract The progress of Industrial Revolution 4.0 has been supported by recent advances
in several domains, and one of the main contributors is the Internet of Things. Smart factories …
in several domains, and one of the main contributors is the Internet of Things. Smart factories …