Zhifang Liang

Orcid: 0000-0002-2525-6104

According to our database1, Zhifang Liang authored at least 14 papers between 2016 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2022
Domain adaptive subspace transfer model for sensor drift compensation in biologically inspired electronic nose.
Expert Syst. Appl., 2022

An Evolutionary Game based Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Wireless Sensor Networks.
CoRR, 2022

2021
A Secure Clustering Protocol With Fuzzy Trust Evaluation and Outlier Detection for Industrial Wireless Sensor Networks.
IEEE Trans. Ind. Informatics, 2021

2020
Convergence analysis of a finite difference scheme for a Riemann-Liouville fractional derivative two-point boundary value problem on an adaptive grid.
J. Comput. Appl. Math., 2020

Drift compensation algorithm based on Time-Wasserstein dynamic distribution alignment.
Proceedings of the 9th IEEE/CIC International Conference on Communications in China, 2020

2019
Wasserstein Distance Learns Domain Invariant Feature Representations for Drift Compensation of E-Nose.
Sensors, 2019

A Novel Subspace Alignment-Based Interference Suppression Method for the Transfer Caused by Different Sample Carriers in Electronic Nose.
Sensors, 2019

Data induced masking representation learning for face data analysis.
Knowl. Based Syst., 2019

2018
Domain Correction Based on Kernel Transformation for Drift Compensation in the E-Nose System.
Sensors, 2018

Study on Interference Suppression Algorithms for Electronic Noses: A Review.
Sensors, 2018

A Dynamic Behavior Monitoring Game-Based Trust Evaluation Scheme for Clustering in Wireless Sensor Networks.
IEEE Access, 2018

2017
Sensor Array Optimization of Electronic Nose for Detection of Bacteria in Wound Infection.
IEEE Trans. Ind. Electron., 2017

2016
Suppression of Strong Background Interference on E-Nose Sensors in an Open Country Environment.
Sensors, 2016

An Intelligent and Automatic control method for Tobacco flue-curing based on Machine Learning.
Int. J. Robotics Autom., 2016


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