Semi-supervised selective ensemble learning based on distance to model for nonlinear soft sensor development
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2016.10.005
Abstract: Data-driven soft sensors have been widely used in process systems for delivering online estimations of hard-to-measure yet important quality-related variables. However, in many data-driven soft sensor applications, the process may be strongly nonlinear, and the… read more here.
Keywords: soft sensor; semi supervised; selective ensemble; method ... See more keywords
A Novel Selective Ensemble Learning Method for Smartphone Sensor-Based Human Activity Recognition Based on Hybrid Diversity Enhancement and Improved Binary Glowworm Swarm Optimization
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3225652
Abstract: Human activity recognition (HAR) is gaining interest with many important applications including ubiquitous computing, health-care services and detection of diseases. Smartphone sensors have high acceptance and adherence in daily life and they provide an alternative… read more here.
Keywords: selective ensemble; ensemble learning; smartphone; base models ... See more keywords
Multi-Output Selective Ensemble Identification of Nonlinear and Nonstationary Industrial Processes.
Sign Up to like & getrecommendations! Published in 2020 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2020.3027701
Abstract: A key characteristic of biological systems is the ability to update the memory by learning new knowledge and removing out-of-date knowledge so that intelligent decision can be made based on the relevant knowledge acquired in… read more here.
Keywords: output selective; selective ensemble; multi output; output ... See more keywords
Diversified Kernel Latent Variable Space and Multi-Objective Optimization for Selective Ensemble Learning-Based Soft Sensor
Sign Up to like & getrecommendations! Published in 2023 at "Applied Sciences"
DOI: 10.3390/app13095224
Abstract: The improvement of data-driven soft sensor modeling methods and techniques for the industrial process has strongly promoted the development of the intelligent process industry. Among them, ensemble learning is an excellent modeling framework. Accuracy and… read more here.
Keywords: based soft; selective ensemble; ensemble learning; soft sensor ... See more keywords