Review on COVID‐19 diagnosis models based on machine learning and deep learning approaches
COVID‐19 is the disease evoked by a new breed of coronavirus called the severe acute
respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a …
respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a …
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 …
Recent Applications and Advances of Migrating Birds Optimization
In this paper, the recent applications and advances of Migrating Birds Optimization (MBO)
algorithm are reviewed. The MBO originated from the V flight shape of the migrating birds in …
algorithm are reviewed. The MBO originated from the V flight shape of the migrating birds in …
Fault diagnosis of train rotating parts based on multi-objective VMD optimization and ensemble learning
Z Jin, D He, R Ma, X Zou, Y Chen, S Shan - Digital Signal Processing, 2022 - Elsevier
Rotating machinery is widely used in various systems of trains, and its health status is
directly related to the reliability of train operation. Therefore, the fault diagnosis of train …
directly related to the reliability of train operation. Therefore, the fault diagnosis of train …
Lemurs optimizer: A new metaheuristic algorithm for global optimization
The Lemur Optimizer (LO) is a novel nature-inspired algorithm we propose in this paper.
This algorithm's primary inspirations are based on two pillars of lemur behavior: leap up and …
This algorithm's primary inspirations are based on two pillars of lemur behavior: leap up and …
Smart home battery for the multi-objective power scheduling problem in a smart home using grey wolf optimizer
The power scheduling problem in a smart home (PSPSH) refers to the timely scheduling
operations of smart home appliances under a set of restrictions and a dynamic pricing …
operations of smart home appliances under a set of restrictions and a dynamic pricing …
Optimization of K-means clustering method using hybrid capuchin search algorithm
Abstract This work presents Hybrid Capuchin Search Algorithm (HCSA) as a meta-heuristic
method to deal with the vexing problems of local optima traps and initialization sensitivity of …
method to deal with the vexing problems of local optima traps and initialization sensitivity of …
Optimization of scientific publications clustering with ensemble approach for topic extraction
The continually developing 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 …
A modified coronavirus herd immunity optimizer for the power scheduling problem
The Coronavirus herd immunity optimizer (CHIO) is a new human-based optimization
algorithm that imitates the herd immunity strategy to eliminate of the COVID-19 disease. In …
algorithm that imitates the herd immunity strategy to eliminate of the COVID-19 disease. In …
[HTML][HTML] A hybrid flower pollination with β-hill climbing algorithm for global optimization
In this paper, the β-hill climbing optimizer is hybridized with the flower pollination algorithm
(FPA) as a local refinement operator for global optimization problems. The proposed method …
(FPA) as a local refinement operator for global optimization problems. The proposed method …