Dechang Pi
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- Scheduling and Optimization Algorithms 39
- Advanced Manufacturing and Logistics Optimization 31
- Assembly Line Balancing Optimization 22
- Artificial Intelligence top 0.5%
- Metaheuristic Optimization Algorithms Research 20
- Anomaly Detection Techniques and Applications 19
- Advanced Graph Neural Networks 13
- Signal Processing top 1%
- Time Series Analysis and Forecasting 13
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- Network Security and Intrusion Detection 12
- Co-authors
- Weishi ShaoZhongshi ShaoIzhar Ahmed KhanBentian LiYue XuJunfu ChenYasir HussainZaheer Ullah Khan
- Journals
- Expert Systems with Applications (21 papers)Knowledge-Based Systems (11 papers)Swarm and Evolutionary Computation (8 papers)
- Partner nations
- ChinaAustraliaUnited Kingdom
In The Last Decade
Dechang Pi
202 papers receiving 4.6k citations
Peers
Comparison fields: 5 of 135
- Industrial and Manufacturing Engineering 1.6k
- Artificial Intelligence 1.7k
- Signal Processing 517
- Computer Networks and Communications 1.1k
- Control and Systems Engineering 702
Countries citing papers authored by Dechang Pi
This map shows the geographic impact of Dechang Pi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dechang Pi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dechang Pi more than expected).
Fields of papers citing papers by Dechang Pi
This network shows the impact of papers produced by Dechang Pi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dechang Pi. The network helps show where Dechang Pi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dechang Pi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 31 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 19 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 6 | |
| 6 | 2024 | 7 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 3 | |
| 9 | 2023 | 64 | |
| 10 | 2023 | 7 | |
| 11 | 2023 | 22 | |
| 12 | 2023 | 1 | |
| 13 | 2023 | 4 | |
| 14 | 2022 | 1 | |
| 15 | 2022 | 19 | |
| 16 | 2021 | 21 | |
| 17 | 2021 | 12 | |
| 18 | 2021 | 87 | |
| 19 | 2020 | 33 | |
| 20 | Information Classification & Coding Technology and Its Development in CIMS | 2002 | 0 |
About Dechang Pi
Dechang Pi is a scholar working on Industrial and Manufacturing Engineering, Artificial Intelligence and Signal Processing, having authored 215 papers that have together received 4.7k indexed citations. Recurring topics across this work include Scheduling and Optimization Algorithms (39 papers), Advanced Manufacturing and Logistics Optimization (31 papers), Assembly Line Balancing Optimization (22 papers), Metaheuristic Optimization Algorithms Research (20 papers), Anomaly Detection Techniques and Applications (19 papers), Advanced Graph Neural Networks (13 papers), Time Series Analysis and Forecasting (13 papers) and Network Security and Intrusion Detection (12 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (1.6k citations), Artificial Intelligence (1.7k citations) and Signal Processing (517 citations). Dechang Pi has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Weishi Shao, Zhongshi Shao, Izhar Ahmed Khan, Bentian Li, Yue Xu, Junfu Chen, Yasir Hussain, Zaheer Ullah Khan, Lin Cui and Nour Moustafa. Their work appears in journals such as Expert Systems with Applications, Knowledge-Based Systems, Swarm and Evolutionary Computation, IEEE Transactions on Automation Science and Engineering and IEEE Access.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.