Publications[Google Scholar]

Representative work

a. Multi-source Information Fusion

Information Fusion 2021
sym

Multi-source information fusion based on rough set theory: A review

Pengfei Zhang, Tianrui Li, Guoqiang, Wang, Chuan Luo, Hongmei Chen, Junbo Zhang, Dexian Wang, Zeng Yu.

  • DOI
  • This paper is to introduce the research progress of Multi-source information fusion based on rough sets including conventional models and techniques.

b. Outlier Detection

Information Fusion 2023
sym

A multi-source information fusion model for outlier detection

Pengfei Zhang, Tianrui Li, Guoqiang Wang, Dexian Wang, Pei Lai, Fan Zhang

  • DOI
  • This is a two-stage model that includes fusion of multiple information sources and outlier detection of fused data.

c. Feature Selection

TFS 2023
sym

A Possibilistic Information Fusion-Based Unsupervised Feature Selection Method Using Information Quality Measures

Pengfei Zhang, Tianrui Li, Zhong Yuan, Zhixuan Deng, Guoqiang Wang, Dexian Wang, Fan Zhang

  • DOI
  • The main goal of most information quality (IQ)-based measures is to combine data provided by multiple information sources to enhance the quality of information essential for decision makers to perform their tasks.

d. Four Diagnostic Methods Integration in Chinese Medicine

CJITWM 2025
sym

智能融合赋能中医四诊合参客观化

张鹏飞, 曾鹏飞, 王德贤, 何昭璇, 曾 芳

  • DOI
  • This paper proposed a framework that leverages multi-granularity learning and multi-source information fusion to address the challenges posed by the multi-source, multimodality, spatiotemporal dynamics, complexity and uncertainty inherent in Chinese Medicine diagnostic data.

Journal and Conference Publications

† denotes equal contribution, †† denotes Corresponding Author

2026

2025

2024

2023

2022

2021

2020

2019