Dechang Pi

6.3k total citations
215 papers, 4.7k citations indexed

About

Dechang Pi is a scholar working on Artificial Intelligence, Industrial and Manufacturing Engineering and Computer Networks and Communications. According to data from OpenAlex, Dechang Pi has authored 215 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 94 papers in Artificial Intelligence, 42 papers in Industrial and Manufacturing Engineering and 40 papers in Computer Networks and Communications. Recurrent topics in Dechang Pi's work include Scheduling and Optimization Algorithms (39 papers), Advanced Manufacturing and Logistics Optimization (31 papers) and Assembly Line Balancing Optimization (22 papers). Dechang Pi is often cited by papers focused on Scheduling and Optimization Algorithms (39 papers), Advanced Manufacturing and Logistics Optimization (31 papers) and Assembly Line Balancing Optimization (22 papers). Dechang Pi collaborates with scholars based in China, Australia and United Kingdom. Dechang Pi's 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 and has published in prestigious journals such as PLoS ONE, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Dechang Pi

202 papers receiving 4.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dechang Pi China 40 1.7k 1.6k 1.1k 702 517 215 4.7k
Salwani Abdullah Malaysia 34 1.7k 1.0× 616 0.4× 616 0.6× 203 0.3× 183 0.4× 146 3.3k
Celal Öztürk Türkiye 26 2.3k 1.4× 385 0.2× 1.4k 1.3× 460 0.7× 161 0.3× 67 4.8k
Mohammed A. Awadallah Jordan 40 2.3k 1.4× 481 0.3× 514 0.5× 795 1.1× 174 0.3× 130 4.8k
Kuangrong Hao China 29 1.2k 0.7× 416 0.3× 753 0.7× 611 0.9× 113 0.2× 262 3.3k
Yongquan Zhou China 41 3.4k 2.0× 956 0.6× 577 0.5× 887 1.3× 158 0.3× 302 6.2k
Alberto Colorni Italy 16 1.1k 0.6× 1.0k 0.6× 473 0.4× 315 0.4× 119 0.2× 41 3.1k
El‐Ghazali Talbi France 30 1.4k 0.8× 1.4k 0.9× 923 0.9× 340 0.5× 69 0.1× 101 3.9k
Yue‐Jiao Gong China 33 2.2k 1.3× 559 0.4× 870 0.8× 411 0.6× 114 0.2× 140 4.5k
Farhad Soleimanian Gharehchopogh Iran 48 4.2k 2.5× 599 0.4× 1.3k 1.2× 919 1.3× 377 0.7× 156 7.7k
Matteo Fischetti Italy 46 845 0.5× 4.6k 2.9× 985 0.9× 720 1.0× 167 0.3× 127 7.0k

Countries citing papers authored by Dechang Pi

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Dechang Pi

This figure shows the co-authorship network connecting the top 25 collaborators of Dechang Pi. A scholar is included among the top collaborators of Dechang Pi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dechang Pi. Dechang Pi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chen, Yang, Dechang Pi, Shengxiang Yang, et al.. (2025). A Dynamic Optimization Framework for Computation Rate Maximization in UAV-Assisted Mobile Edge Computing. IEEE Transactions on Vehicular Technology. 74(7). 11395–11409. 5 indexed citations
2.
Zhang, Zeyu, Zhongshi Shao, Weishi Shao, Jianrui Chen, & Dechang Pi. (2024). MRLM: A meta-reinforcement learning-based metaheuristic for hybrid flow-shop scheduling problem with learning and forgetting effects. Swarm and Evolutionary Computation. 85. 101479–101479. 31 indexed citations
3.
Khan, Izhar Ahmed, et al.. (2024). A context-aware zero trust-based hybrid approach to IoT-based self-driving vehicles security. Ad Hoc Networks. 167. 103694–103694. 4 indexed citations
4.
Shao, Zhongshi, Weishi Shao, Jianrui Chen, & Dechang Pi. (2024). A feedback learning-based selection hyper-heuristic for distributed heterogeneous hybrid blocking flow-shop scheduling problem with flexible assembly and setup time. Engineering Applications of Artificial Intelligence. 131. 107818–107818. 19 indexed citations
5.
Shao, Zhongshi, et al.. (2024). Joint scheduling of hybrid flow-shop with limited automatic guided vehicles: A hierarchical learning-based swarm optimizer. Computers & Industrial Engineering. 198. 110686–110686. 2 indexed citations
6.
Zhang, Ke, et al.. (2024). A novel fine-grained rumor detection algorithm with attention mechanism. Neurocomputing. 583. 127595–127595. 6 indexed citations
7.
Chen, Yang, Dechang Pi, Shengxiang Yang, et al.. (2024). A multi-strategy optimizer for energy minimization of multi-UAV-assisted mobile edge computing. Swarm and Evolutionary Computation. 91. 101748–101748. 7 indexed citations
8.
Pi, Dechang, et al.. (2024). Path optimization algorithm for mobile sink in wireless sensor network. Expert Systems with Applications. 255. 124801–124801. 2 indexed citations
9.
Pi, Dechang, et al.. (2024). An Asymmetric Dominated Multiobjective Optimization Algorithm for Reducing Energy Consumption of WSN Operation. IEEE Sensors Journal. 24(14). 23075–23087. 3 indexed citations
10.
Khan, Izhar Ahmed, Imran Razzak, Dechang Pi, et al.. (2023). Fed-Inforce-Fusion: A federated reinforcement-based fusion model for security and privacy protection of IoMT networks against cyber-attacks. Information Fusion. 101. 102002–102002. 64 indexed citations
11.
Xu, Yue, Dechang Pi, Yang Chen, et al.. (2023). A reinforcement learning-based multi-objective optimization in an interval and dynamic environment. Knowledge-Based Systems. 280. 111019–111019. 7 indexed citations
12.
Pi, Dechang, et al.. (2023). Synchronization of time scales switched complex networks via impulsive couplings. Mathematical Methods in the Applied Sciences. 46(9). 10624–10641. 1 indexed citations
13.
Pan, Yue, et al.. (2022). DUFuse: Deep U-Net for visual and infrared images fusion. Journal of Ambient Intelligence and Humanized Computing. 14(9). 12549–12561. 1 indexed citations
14.
Xu, Yue, Dechang Pi, Shengxiang Yang, et al.. (2022). An Angle-Based Bi-Objective Optimization Algorithm for Redundancy Allocation in Presence of Interval Uncertainty. IEEE Transactions on Automation Science and Engineering. 20(1). 271–284. 19 indexed citations
15.
Pan, Yue, et al.. (2021). FDPPGAN: remote sensing image fusion based on deep perceptual patchGAN. Neural Computing and Applications. 33(15). 9589–9605. 12 indexed citations
16.
Khan, Izhar Ahmed, Nour Moustafa, Dechang Pi, et al.. (2021). An Enhanced Multi-Stage Deep Learning Framework for Detecting Malicious Activities From Autonomous Vehicles. IEEE Transactions on Intelligent Transportation Systems. 23(12). 25469–25478. 87 indexed citations
17.
Liu, Yongzhi, et al.. (2016). Research on the Application of the Segmentation Based on Key Points in the Power Consumption of Wireless Sensor. Journal of Applied Science and Engineering. 19(1). 109–112. 1 indexed citations
18.
Pi, Dechang, et al.. (2013). Novel method for hurricane trajectory prediction based on data mining. Natural hazards and earth system sciences. 13(12). 3211–3220. 5 indexed citations
19.
Pi, Dechang. (2008). Outlier Detection Algorithm Based on Neighborhood and Density. Journal of Jilin University. 1 indexed citations
20.
Pi, Dechang, et al.. (2008). An improved C-means clustering algorithm.. Computer Systems: Science & Engineering. 23. 2 indexed citations

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.

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