Edward Keedwell

2.9k total citations
96 papers, 1.5k citations indexed

About

Edward Keedwell is a scholar working on Civil and Structural Engineering, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Edward Keedwell has authored 96 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Civil and Structural Engineering, 27 papers in Artificial Intelligence and 24 papers in Computational Theory and Mathematics. Recurrent topics in Edward Keedwell's work include Water Systems and Optimization (41 papers), Advanced Multi-Objective Optimization Algorithms (18 papers) and Water resources management and optimization (15 papers). Edward Keedwell is often cited by papers focused on Water Systems and Optimization (41 papers), Advanced Multi-Objective Optimization Algorithms (18 papers) and Water resources management and optimization (15 papers). Edward Keedwell collaborates with scholars based in United Kingdom, Netherlands and United States. Edward Keedwell's co-authors include Dragan Savić, Soon‐Thiam Khu, Slobodan Djordjević, Albert Chen, Michele Guidolin, Arjun Narayanan, Zoran Kapelan, Kent McClymont, Raziyeh Farmani and Ajit Narayanan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Water Research and Information Sciences.

In The Last Decade

Edward Keedwell

89 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Edward Keedwell United Kingdom 21 447 350 317 297 273 96 1.5k
Maarten Keijzer Denmark 13 166 0.4× 197 0.6× 316 1.0× 328 1.1× 550 2.0× 34 1.4k
Jarosław J. Napiórkowski Poland 25 192 0.4× 458 1.3× 747 2.4× 573 1.9× 508 1.9× 74 2.0k
Tao Bai China 21 224 0.5× 263 0.8× 505 1.6× 125 0.4× 144 0.5× 99 1.7k
Leonardo Goliatt Brazil 18 105 0.2× 137 0.4× 109 0.3× 213 0.7× 305 1.1× 103 1.1k
Feilin Zhu China 24 244 0.5× 505 1.4× 607 1.9× 249 0.8× 73 0.3× 68 1.6k
Razi Sheikholeslami Iran 19 373 0.8× 119 0.3× 182 0.6× 179 0.6× 331 1.2× 42 1.2k
Cedric Jean-Marie Sallaberry United States 16 349 0.8× 117 0.3× 77 0.2× 323 1.1× 61 0.2× 41 1.9k
David Hadka United States 11 434 1.0× 302 0.9× 536 1.7× 210 0.7× 283 1.0× 20 1.6k
Yu Han China 20 141 0.3× 109 0.3× 73 0.2× 125 0.4× 115 0.4× 168 1.4k
Elmar Plischke Germany 14 340 0.8× 87 0.2× 113 0.4× 271 0.9× 80 0.3× 35 1.6k

Countries citing papers authored by Edward Keedwell

Since Specialization
Citations

This map shows the geographic impact of Edward Keedwell'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 Edward Keedwell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edward Keedwell more than expected).

Fields of papers citing papers by Edward Keedwell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Edward Keedwell. 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 Edward Keedwell. The network helps show where Edward Keedwell may publish in the future.

Co-authorship network of co-authors of Edward Keedwell

This figure shows the co-authorship network connecting the top 25 collaborators of Edward Keedwell. A scholar is included among the top collaborators of Edward Keedwell 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 Edward Keedwell. Edward Keedwell 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.
Farmani, Raziyeh, et al.. (2025). Advancements in Burst Localization through Real-Time Hydraulic Gradient Analysis with Deep Neural Networks in Complex Water Transmission Systems. Journal of Water Resources Planning and Management. 151(5). 1 indexed citations
2.
Farmani, Raziyeh, et al.. (2024). Real-Time Burst Localization in Complex Water Transmission Lines Using Hydraulic Gradient Analysis. SHILAP Revista de lepidopterología. 106–106. 1 indexed citations
3.
Moraglio, Alberto, et al.. (2024). Applying a Quantum Annealer to the Traffic Assignment Problem. Proceedings of the Genetic and Evolutionary Computation Conference. 814–822. 1 indexed citations
4.
Farmani, Raziyeh, et al.. (2024). A Novel Multi-Step Forecasting-Based Approach for Enhanced Burst Detection in Water Distribution Systems. SHILAP Revista de lepidopterología. 146–146.
5.
Keedwell, Edward, et al.. (2024). An explainable machine learning approach to the prediction of pipe failure using minimum night flow. Journal of Hydroinformatics. 26(7). 1490–1504. 1 indexed citations
6.
Keedwell, Edward, et al.. (2023). Understanding district metered area level leakage using explainable machine learning. IOP Conference Series Earth and Environmental Science. 1136(1). 12040–12040. 3 indexed citations
7.
Farmani, Raziyeh, et al.. (2022). Online leakage detection system based on EWMA-enhanced Tukey method for water distribution systems. Journal of Hydroinformatics. 25(1). 51–69. 8 indexed citations
8.
Yates, William B. & Edward Keedwell. (2020). Offline Learning with a Selection Hyper-Heuristic: An Application to Water Distribution Network Optimisation. Evolutionary Computation. 29(2). 187–210. 7 indexed citations
9.
Keedwell, Edward, et al.. (2019). Human-evolutionary problem solving through gamification of a bin-packing problem. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 1465–1473. 9 indexed citations
10.
Keedwell, Edward, et al.. (2019). A statistical analysis on the effect of preceding dry weather on sewer blockages in South Wales. Water Science & Technology. 80(12). 2381–2391. 6 indexed citations
11.
Keedwell, Edward, et al.. (2018). Evaluating Image Classification Techniques for Improved Urban Wastewater System Model Calibration. EGUGA. 16327. 1 indexed citations
12.
Kapelan, Zoran, et al.. (2017). Short-term forecasting of turbidity in trunk main networks. Water Research. 124. 67–76. 33 indexed citations
13.
Guidolin, Michele, et al.. (2016). A weighted cellular automata 2D inundation model for rapid flood analysis. Environmental Modelling & Software. 84. 378–394. 189 indexed citations
14.
Bailey, James, Edward Keedwell, Slobodan Djordjević, et al.. (2015). Predictive risk modelling of real-world wastewater network incidents. Procedia Engineering. 119. 1288–1298. 11 indexed citations
15.
Keedwell, Edward, et al.. (2014). Multi-Objective Pipe Smoothing Genetic Algorithm For Water Distribution Network Design. CUNY Academic Works (City University of New York). 1 indexed citations
16.
Schellart, Alma, Nuno Simões, Li-Pen Wang, et al.. (2011). Urban pluvial flood modelling with real time rainfall information – UK case studies. Open Research Exeter (University of Exeter). 8 indexed citations
17.
Guo, Yufeng, et al.. (2008). Optimal Design of Sewer Networks using hybrid cellular automata and genetic algorithm. 10 indexed citations
18.
Khu, Soon‐Thiam & Edward Keedwell. (2005). Introducing more choices (flexibility) in the upgrading of water distribution networks: the New York city tunnel network example. Engineering Optimization. 37(3). 291–305. 23 indexed citations
19.
Keedwell, Edward & Arjun Narayanan. (2005). Discovering Gene Networks with a Neural-Genetic Hybrid. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2(3). 231–242. 59 indexed citations
20.
Keedwell, Edward, Ajit Narayanan, & Dragan Savić. (1999). Using genetic algorithms to extract rules from trained neural networks. Genetic and Evolutionary Computation Conference. 793–793. 8 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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