A survey on evolutionary multiobjective feature selection in classification: approaches, applications, and challenges
Maximizing the classification accuracy and minimizing the number of selected features are
two primary objectives in feature selection, which is inherently a multiobjective task …
two primary objectives in feature selection, which is inherently a multiobjective task …
Recent advances in multi-objective grey wolf optimizer, its versions and applications
In this work, a comprehensive review of the multi-objective grey wolf optimizer (MOGWO) is
provided. In multi-objective optimization (MO), more than one objective function must be …
provided. In multi-objective optimization (MO), more than one objective function must be …
A multi-objective evolutionary algorithm with interval based initialization and self-adaptive crossover operator for large-scale feature selection in classification
Feature selection (FS) is an important data pre-processing technique in classification. In
most cases, FS can improve classification accuracy and reduce feature dimension, so it can …
most cases, FS can improve classification accuracy and reduce feature dimension, so it can …
[HTML][HTML] Hybrid deep CNN-SVR algorithm for solar radiation prediction problems in Queensland, Australia
This study proposes a new hybrid deep learning (DL) model, the called CSVR, for Global
Solar Radiation (GSR) predictions by integrating Convolutional Neural Network (CNN) with …
Solar Radiation (GSR) predictions by integrating Convolutional Neural Network (CNN) with …
A landscape-aware particle swarm optimization for parameter identification of photovoltaic models
Photovoltaic (PV) systems play a significant role in power systems since they can convert
solar energy directly into electricity. Their conversion performance depends mainly on the …
solar energy directly into electricity. Their conversion performance depends mainly on the …
[HTML][HTML] An interpretable multi-stage forecasting framework for energy consumption and CO2 emissions for the transportation sector
The transportation sector is deemed one of the primary sources of energy consumption and
greenhouse gases throughout the world. To realise and design sustainable transport, it is …
greenhouse gases throughout the world. To realise and design sustainable transport, it is …
[HTML][HTML] An optimized and efficient android malware detection framework for future sustainable computing
Android-based smart devices cater to services in almost every aspect of our lives like
personal, professional, social, banking, business, etc. However, people with increasingly …
personal, professional, social, banking, business, etc. However, people with increasingly …
Prediction of gas explosion pressures: A machine learning algorithm based on KPCA and an optimized LSSVM
K Zhang, K Zhang, R Bao - Journal of Loss Prevention in the Process …, 2023 - Elsevier
A gas explosion, as a common accident in public life and industry, poses a great threat to the
safety of life and property. The determination and prediction of gas explosion pressures are …
safety of life and property. The determination and prediction of gas explosion pressures are …
Multi-objective binary grey wolf optimization for feature selection based on guided mutation strategy
Feature selection aims to choose a subset of features with minimal feature-feature
correlation and maximum feature-class correlation, which can be considered as a multi …
correlation and maximum feature-class correlation, which can be considered as a multi …
[HTML][HTML] Feature selection strategy for machine learning methods in building energy consumption prediction
Building energy management systems (BEMS) have somewhat standardised building
energy consumption data formats, thereby enhancing their compatibility with the relevant ML …
energy consumption data formats, thereby enhancing their compatibility with the relevant ML …