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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 …
A comprehensive review of bat inspired algorithm: variants, applications, and hybridization
Bat algorithm (BA) is one of the promising metaheuristic algorithms. It proved its efficiency in
dealing with various optimization problems in diverse fields, such as power and energy …
dealing with various optimization problems in diverse fields, such as power and energy …
[HTML][HTML] Hybrid CNN and XGBoost model tuned by modified arithmetic optimization algorithm for COVID-19 early diagnostics from X-ray images
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 …
pandemic since its emergence. One of the most important ways to control the spread of this …
[HTML][HTML] Tuning machine learning models using a group search firefly algorithm for credit card fraud detection
Recent advances in online payment technologies combined with the impact of the COVID-
19 global pandemic has led to a significant escalation in the number of online transactions …
19 global pandemic has led to a significant escalation in the number of online transactions …
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 …
Bee optimization based random double adaptive whale optimization model for task scheduling in cloud computing environment
N Manikandan, N Gobalakrishnan… - Computer Communications, 2022 - Elsevier
Cloud computing is the computing technology that offers dynamically scalable and flexible
computing resources. Task scheduling in the cloud system is the major problem that needs …
computing resources. Task scheduling in the cloud system is the major problem that needs …
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] Hybrid fruit-fly optimization algorithm with k-means for text document clustering
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 …
the unstructured format of text data, extracting relevant information and its analysis becomes …
Novel improved salp swarm algorithm: An application for feature selection
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 …
sensors and it is often the case that decisions are taken based on them in a more or less …