Analysis of Extreme Learning Machines (ELMs) for intelligent intrusion detection systems: A survey
The ever-increasing interconnectedness of our world, fueled by technological
advancements across industries, has made network security a paramount concern. This …
advancements across industries, has made network security a paramount concern. This …
Cloud computing load prediction by decomposition reinforced attention long short-term memory network optimized by modified particle swarm optimization algorithm
Computer resources provision over the internet resulted in the wide spread usage of cloud
computing paradigm. With the use of such resources come certain challenges that can …
computing paradigm. With the use of such resources come certain challenges that can …
Bayesian extreme learning machines for hydrological prediction uncertainty
In recent years, extreme learning machines (ELM) have been used to accurately predict a
variety of hydrological variables (eg, streamflow, precipitation, river water quality). Using the …
variety of hydrological variables (eg, streamflow, precipitation, river water quality). Using the …
A comparative evaluation of nature-inspired algorithms for feature selection problems
Feature selection is a critical component of machine learning and data mining which
addresses challenges like irrelevance, noise, redundancy in large-scale data etc., which …
addresses challenges like irrelevance, noise, redundancy in large-scale data etc., which …
Detecting Parkinson's disease from shoe-mounted accelerometer sensors using convolutional neural networks optimized with modified metaheuristics
L Jovanovic, R Damaševičius, R Matic, M Kabiljo… - PeerJ Computer …, 2024 - peerj.com
Neurodegenerative conditions significantly impact patient quality of life. Many conditions do
not have a cure, but with appropriate and timely treatment the advance of the disease could …
not have a cure, but with appropriate and timely treatment the advance of the disease could …
Prediction of Ship Painting Man-Hours Based on Selective Ensemble Learning
H Bu, Z Ge, X Zhu, T Yang, H Zhou - Coatings, 2024 - mdpi.com
The precise prediction of painting man-hours is significant to ensure the efficient scheduling
of shipyard production and maintain a stable production pace, which directly impacts …
of shipyard production and maintain a stable production pace, which directly impacts …
Novel hybrid classifier based on fuzzy type-III decision maker and ensemble deep learning model and improved chaos game optimization
This paper presents a unique hybrid classifier that combines deep neural networks with a
type-III fuzzy system for decision-making. The ensemble incorporates ResNet-18, Efficient …
type-III fuzzy system for decision-making. The ensemble incorporates ResNet-18, Efficient …
Employee reviews sentiment classification using BERT encoding and AdaBoost classifier tuned by modified PSO algorithm
Sentiment analysis of the employee reviews is very important to understand the satisfaction
in the company, predict the engagement of the employees, identify the risk of employee …
in the company, predict the engagement of the employees, identify the risk of employee …
Classification of Fritillaria using a portable near-infrared spectrometer and fuzzy generalized singular value decomposition
X Wu, Y Wang, B Wu, J Sun - Industrial Crops and Products, 2024 - Elsevier
Fritillaria is a popular Chinese medicinal crop known for its medicinal value. However, the
chemical composition and medicinal value of Fritillaria can vary significantly depending on …
chemical composition and medicinal value of Fritillaria can vary significantly depending on …
An improved Differential evolution with Sailfish optimizer (DESFO) for handling feature selection problem
As a preprocessing for machine learning and data mining, Feature Selection plays an
important role. Feature selection aims to streamline high-dimensional data by eliminating …
important role. Feature selection aims to streamline high-dimensional data by eliminating …