Best-worst individuals driven multiple-layered differential evolution
Conventional differential evolution (DE) algorithms have been widely used for optimisation
problems but suffer from low performance and premature convergence. Hence, researchers …
problems but suffer from low performance and premature convergence. Hence, researchers …
The link between the nature of the human–companion animal relationship and well-being outcomes in companion animal owners
Simple Summary Past research regarding the impact of companion animals on well-being
has yielded variable results, with some studies finding that companion animals have a …
has yielded variable results, with some studies finding that companion animals have a …
High-order polynomial interpolation with CNN: A robust approach for missing data imputation
The presence of missing data poses a significant challenge in knowledge extraction, where
completeness and quality are crucial factors. The decision to ignore records with missing …
completeness and quality are crucial factors. The decision to ignore records with missing …
[HTML][HTML] CC-GAIN: Clustering and classification-based generative adversarial imputation network for missing electricity consumption data imputation
J Hwang, D Suh - Expert Systems with Applications, 2024 - Elsevier
The widespread use of data across various fields has made missing data imputation
technology a crucial tool. High-quality data is essential for effective energy management in …
technology a crucial tool. High-quality data is essential for effective energy management in …
Evolution learning method to derive missing elements and optimal classification under the connection hesitant fuzzy environment
W Zhou, M Liu - Computers & Industrial Engineering, 2024 - Elsevier
Generally, in the qualitative decision-making process, the attributes are independent of each
other, thus the given attributes' evaluation data could ignore their connection relationships …
other, thus the given attributes' evaluation data could ignore their connection relationships …
A partition-based convergence framework for population-based optimization algorithms
Population-based optimization algorithms, such as genetic algorithm and particle swarm
optimization, have become a class of important algorithms for solving global optimization …
optimization, have become a class of important algorithms for solving global optimization …
Advancing Missing Data Imputation in Time-Series: A Review and Proposed Prototype
K Thakur, H Kumar - … on Emerging Trends in Networks and …, 2023 - ieeexplore.ieee.org
Completeness and quality of data are crucial for any type of data analysis and play a vital
role in time series forecasting. However, a common challenge in time series forecasting is …
role in time series forecasting. However, a common challenge in time series forecasting is …
GMA: Gap Imputing Algorithm for time series missing values
Data collected from the environment in computer engineering may include missing values
due to various factors, such as lost readings from sensors caused by communication errors …
due to various factors, such as lost readings from sensors caused by communication errors …
PEDI-GAN: power equipment data imputation based on generative adversarial networks with auxiliary encoder
Smart grids commonly rely on analyzing sensor data to monitor power equipment. However,
these sensor data can suffer varying levels of loss or corruption due to complex …
these sensor data can suffer varying levels of loss or corruption due to complex …
[HTML][HTML] Predictive models for Alzheimer's disease diagnosis and MCI identification: The use of cognitive scores and artificial intelligence algorithms
SA Sadegh-Zadeh, MJ Nazari, M Aljamaeen… - NPG Neurologie …, 2024 - Elsevier
The paper presents a comprehensive study on predictive models for Alzheimer's disease
(AD) and mild cognitive impairment (MCI) diagnosis, implementing a combination of …
(AD) and mild cognitive impairment (MCI) diagnosis, implementing a combination of …