D. J. Evans

3.2k total citations
241 papers, 2.2k citations indexed

About

D. J. Evans is a scholar working on Computational Theory and Mathematics, Numerical Analysis and Computer Networks and Communications. According to data from OpenAlex, D. J. Evans has authored 241 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 148 papers in Computational Theory and Mathematics, 93 papers in Numerical Analysis and 50 papers in Computer Networks and Communications. Recurrent topics in D. J. Evans's work include Matrix Theory and Algorithms (121 papers), Numerical methods for differential equations (60 papers) and Electromagnetic Scattering and Analysis (36 papers). D. J. Evans is often cited by papers focused on Matrix Theory and Algorithms (121 papers), Numerical methods for differential equations (60 papers) and Electromagnetic Scattering and Analysis (36 papers). D. J. Evans collaborates with scholars based in United Kingdom, China and Greece. D. J. Evans's co-authors include Graham M. Megson, Xiaofan Yang, M. Hatzopoulos, K. R. Raslan, K. Murugesan, A. Hadjidimos, Abdul Rahman Abdullah, Hong‐Jian Lai, Changjun Li and Marjan Gušev and has published in prestigious journals such as NeuroImage, The Journal of the Acoustical Society of America and Computer Methods in Applied Mechanics and Engineering.

In The Last Decade

D. J. Evans

226 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. J. Evans United Kingdom 22 929 772 672 461 327 241 2.2k
Hans D. Mittelmann United States 25 691 0.7× 588 0.8× 264 0.4× 235 0.5× 603 1.8× 127 2.3k
Fred T. Krogh United States 12 533 0.6× 314 0.4× 404 0.6× 158 0.3× 192 0.6× 42 1.5k
W. L. Miranker United States 17 507 0.5× 316 0.4× 308 0.5× 190 0.4× 260 0.8× 56 1.3k
Daniel Kreßner Switzerland 25 1.5k 1.6× 777 1.0× 115 0.2× 182 0.4× 738 2.3× 148 2.8k
J. A. Scott United Kingdom 22 867 0.9× 420 0.5× 111 0.2× 301 0.7× 420 1.3× 145 1.8k
Hans Sagan United States 12 335 0.4× 178 0.2× 226 0.3× 164 0.4× 258 0.8× 32 1.9k
Bo Kågström Sweden 26 1.5k 1.6× 703 0.9× 360 0.5× 144 0.3× 144 0.4× 97 2.2k
Zhimin Zhang China 19 201 0.2× 472 0.6× 133 0.2× 262 0.6× 422 1.3× 108 1.3k
Didier Henrion France 33 1.3k 1.4× 1.3k 1.7× 226 0.3× 293 0.6× 305 0.9× 202 4.2k
Bassam Bamieh United States 31 397 0.4× 225 0.3× 1.0k 1.5× 458 1.0× 729 2.2× 171 4.6k

Countries citing papers authored by D. J. Evans

Since Specialization
Citations

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

Fields of papers citing papers by D. J. Evans

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. J. Evans. 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 D. J. Evans. The network helps show where D. J. Evans may publish in the future.

Co-authorship network of co-authors of D. J. Evans

This figure shows the co-authorship network connecting the top 25 collaborators of D. J. Evans. A scholar is included among the top collaborators of D. J. Evans 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 D. J. Evans. D. J. Evans 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.
Yang, Xiaofan, et al.. (2005). On the recursive sequence Xn = axn-1+bxn-2/c+dxn-1xn-2. Nottingham Trent University's Institutional Repository (Nottingham Trent Repository). 15 indexed citations
2.
Yang, Xiaofan, Graham M. Megson, & D. J. Evans. (2004). Locally twisted cubes are 4-pancyclic. Applied Mathematics Letters. 17(8). 919–925. 50 indexed citations
3.
Evans, D. J., et al.. (2002). Explicit group AOR method for solving elliptic partial differential equations. Neural, Parallel & Scientific Computations archive. 10(4). 411–422. 9 indexed citations
4.
Evans, D. J., et al.. (2001). The AOR iterative method for new preconditioned linear systems. Journal of Computational and Applied Mathematics. 132(2). 461–466. 44 indexed citations
5.
Evans, D. J., et al.. (1996). On preconditioned msor iterations. International Journal of Computer Mathematics. 59(3-4). 251–257. 1 indexed citations
6.
Evans, D. J. & H. Y. Y. Sanossian. (1996). A hierarchical artificial neural network architecture for English character recognition. Neural, Parallel & Scientific Computations archive. 4(4). 397–404. 2 indexed citations
7.
Margaritis, Konstantinos G., et al.. (1995). On multi-property set operations using neural networks and systolic arrays. Neural, Parallel & Scientific Computations archive. 3(1). 1–13.
8.
Margaritis, Konstantinos G. & D. J. Evans. (1994). Iterative matrix inversion on a systolic array: a case of algorithm integration. International Journal of Computer Mathematics. 51(1-2). 95–106. 3 indexed citations
9.
Evans, D. J.. (1993). Design of parallel matrix algorithms. Cambridge University Press eBooks. 123–147. 1 indexed citations
10.
Evans, D. J., et al.. (1989). Parallel computing : methods, algorithms, and applications : proceedings of the International Meeting on Parallel Computing, Verona, Italy, 28-30 September 1988. 1 indexed citations
11.
Evans, D. J., et al.. (1989). A note on the SOR and CG methods for large least squares problems. Linear Algebra and its Applications. 121. 163–170. 2 indexed citations
12.
Evans, D. J.. (1988). Designing efficient systolic algorithms for VLSI parallel processor arrays. Oxford University Press eBooks. 261–281. 1 indexed citations
13.
Evans, D. J., et al.. (1988). On the convergence of the SAOR method and the error bounds for its acceleration. Journal of Computational and Applied Mathematics. 23(3). 267–279. 3 indexed citations
14.
Evans, D. J., et al.. (1988). Analysis of a symmetric extrapolated iterative method for solving linear systems. Linear Algebra and its Applications. 103. 149–173. 3 indexed citations
15.
Evans, D. J.. (1985). Parallel algorithms in computational linear algebra. 55–79. 7 indexed citations
16.
Avdelas, G., D. J. Evans, & A. Hadjidimos. (1981). Second order Chebyshev semi-iteration in connection with p-parametric E.A.D.I. schemes. Journal of Computational and Applied Mathematics. 7(4). 261–266. 1 indexed citations
17.
Evans, D. J.. (1981). Alternating direction implicit preconditioning methods for self adjoint elliptic differential equations. Computers & Mathematics with Applications. 7(2). 151–158. 2 indexed citations
18.
Evans, D. J., et al.. (1981). On the acceleration of the preconditioned simultaneous displacement method. Mathematics and Computers in Simulation. 23(2). 191–198. 3 indexed citations
19.
Benson, Austin R. & D. J. Evans. (1979). A normalised algorithm for the solution of symmetric general five-term linear systems of semi-bandwidth M. Journal of Computational and Applied Mathematics. 5(4). 299–304. 6 indexed citations
20.
Evans, D. J.. (1962). Numerical Studies of Implicit Iterative Methods for Solving Elliptic Difference Equations.. IFIP Congress. 132–140. 1 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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