Recent advances in Grey Wolf Optimizer, its versions and applications
The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
Multiclass Paddy Disease Detection Using Filter Based Feature Transformation Technique
Pests and diseases are the big issues in paddy production and they make the farmers to
lose around 20% of rice yield world-wide. Identification of rice leaves diseases at early stage …
lose around 20% of rice yield world-wide. Identification of rice leaves diseases at early stage …
A hierarchical multi-leadership sine cosine algorithm to dissolving global optimization and data classification: The COVID-19 case study
M Zhong, J Wen, J Ma, H Cui, Q Zhang… - Computers in Biology and …, 2023 - Elsevier
Abstract The Sine Cosine Algorithm (SCA) is an outstanding optimizer that is appreciably
used to dissolve complicated real-world problems. Nevertheless, this algorithm lacks …
used to dissolve complicated real-world problems. Nevertheless, this algorithm lacks …
A multi-factor combination prediction model of carbon emissions based on improved CEEMDAN
G Li, H Wu, H Yang - Environmental Science and Pollution Research, 2024 - Springer
As the global greenhouse effect intensifies, carbon emissions are gradually becoming a hot
topic of discussion. Accurate carbon emissions prediction is an important foundation to …
topic of discussion. Accurate carbon emissions prediction is an important foundation to …
[HTML][HTML] A novel improved lemurs optimization algorithm for feature selection problems
The irrelevant and repeated features in high-dimensional datasets can negatively affect the
final performance and accuracy of classification-based models. Therefore, feature selection …
final performance and accuracy of classification-based models. Therefore, feature selection …
Enhancing rice leaf disease classification: a customized convolutional neural network approach
In modern agriculture, correctly identifying rice leaf diseases is crucial for maintaining crop
health and promoting sustainable food production. This study presents a detailed …
health and promoting sustainable food production. This study presents a detailed …
EEGAlzheimer'sNet: Development of transformer-based attention long short term memory network for detecting Alzheimer disease using EEG signal
D kumar Ravikanti, S Saravanan - Biomedical Signal Processing and …, 2023 - Elsevier
A previous diagnosis of Alzheimer's disease (AD) in its initial stages is needed for patient
care because it helps patients adopt preventative measures before irreversible brain …
care because it helps patients adopt preventative measures before irreversible brain …
Optimization of scientific publications clustering with ensemble approach for topic extraction
The continually develo** Internet generates a considerable amount of text data. When
attempting to extract general topics or themes from a massive corpus of documents, dealing …
attempting to extract general topics or themes from a massive corpus of documents, dealing …
Metaheuristic algorithms for 6G wireless communications: Recent advances and applications
The widespread distribution of applications and devices, coupled with the vast array of
mobile data, technologies, and architectures within Sixth Generation (6G) networks …
mobile data, technologies, and architectures within Sixth Generation (6G) networks …
Arrhythmia classification using ECG signal: A meta-heuristic improvement of optimal weighted feature integration and attention-based hybrid deep learning model
WS Admass, GA Bogale - Biomedical Signal Processing and Control, 2024 - Elsevier
In healthcare facilities, the most common and least expensive diagnostic tool for monitoring
electrical signals in the heart is the Electrocardiogram (ECG). Arrhythmia is nothing but …
electrical signals in the heart is the Electrocardiogram (ECG). Arrhythmia is nothing but …