Improving Recognition Accuracy of Pesticides in Groundwater by Applying TrAdaBoost Transfer Learning Method
Accurate and rapid prediction of pesticides in groundwater is important to protect human health. Thus, an electronic nose was used to recognize pesticides in groundwater. However, the e-nose response signals for pesticides are different in groundwater samples from various regions, so a prediction mo...
Main Authors: | Donghui Chen, Bingyang Wang, Xiao Yang, Xiaohui Weng, Zhiyong Chang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-04-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/23/8/3856 |
Similar Items
-
ALTRA: Cross-Project Software Defect Prediction via Active Learning and Tradaboost
by: Zhidan Yuan, et al.
Published: (2020-01-01) -
A Data-Efficient Building Electricity Load Forecasting Method Based on Maximum Mean Discrepancy and Improved TrAdaBoost Algorithm
by: Kangji Li, et al.
Published: (2022-11-01) -
An instance-based deep transfer learning method for quality identification of Longjing tea from multiple geographical origins
by: Cheng Zhang, et al.
Published: (2023-03-01) -
Classification of motor imagery electroencephalogram signals by using adaptive cross-subject transfer learning
by: Jin Feng, et al.
Published: (2022-12-01) -
An improved AdaBoost algorithm for identification of lung cancer based on electronic nose
by: Lijun Hao, et al.
Published: (2023-03-01)