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
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 …
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 …
Hybridized sine cosine algorithm with convolutional neural networks dropout regularization application
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 …
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
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 …
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
Cloud computing represents relatively new paradigm of utilizing remote computing
resources and is becoming increasingly important and popular technology, that supports on …
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
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 …
amount of data for processing. Tasks that require an instant response, especially with …
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 …
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 …
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
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 …