An Improved Algorithm of Drift Compensation for Olfactory Sensors
This research mainly studies the semi-supervised learning algorithm of different domain data in machine olfaction, also known as sensor drift compensation algorithm. Usually for this kind of problem, it is difficult to obtain better recognition results by directly using the semi-supervised learning...
Main Authors: | Siyu Lu, Jialiang Guo, Shan Liu, Bo Yang, Mingzhe Liu, Lirong Yin, Wenfeng Zheng |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-09-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/12/19/9529 |
Similar Items
-
Online Sensor Drift Compensation for E-Nose Systems Using Domain Adaptation and Extreme Learning Machine
by: Zhiyuan Ma, et al.
Published: (2018-03-01) -
A Semi-Supervised Extreme Learning Machine Algorithm Based on the New Weighted Kernel for Machine Smell
by: Wei Dang, et al.
Published: (2022-09-01) -
Cross-Domain Active Learning for Electronic Nose Drift Compensation
by: Fangyu Sun, et al.
Published: (2022-08-01) -
Balanced Distribution Adaptation for Metal Oxide Semiconductor Gas Sensor Array Drift Compensation
by: Zongze Jiang, et al.
Published: (2021-05-01) -
Tiny Machine Learning Zoo for Long-Term Compensation of Pressure Sensor Drifts
by: Danilo Pau, et al.
Published: (2023-11-01)