Larry J. Eshelman

7.1k citations
40 papers · 2.3k indexed · 1 hit paper · h-index 20
Topics
Evolutionary Algorithms and Applications (9 papers)Metaheuristic Optimization Algorithms Research (8 papers)Acute Kidney Injury Research (7 papers)

In The Last Decade

Larry J. Eshelman

39 papers receiving 2.0k citations

Hit Papers

A study of control parameters affecting online performanc...19892026200120131989200400600

Peers

Larry J. Eshelman
Comparison fields: 5 of 146
  • Artificial Intelligence 1.4k
  • Computational Theory and Mathematics 625
  • Control and Systems Engineering 178
  • Industrial and Manufacturing Engineering 176
  • Computer Vision and Pattern Recognition 139
Replace Miloš Hauskrecht with:
Miloš Hauskrecht United States
Ivo Couckuyt Belgium
P. M. Pardalos United States
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Larry J. Eshelman relative to Miloš Hauskrecht United States Miloš Hauskrecht's profile →
Citations per field
00.5×4.6×
Miloš Hauskrecht · 1×
Citations per year

Countries citing papers authored by Larry J. Eshelman

Since Specialization
Citations

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

Fields of papers citing papers by Larry J. Eshelman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Larry J. Eshelman

This figure shows the co-authorship network connecting the top 25 collaborators of Larry J. Eshelman. A scholar is included among the top collaborators of Larry J. Eshelman 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 Larry J. Eshelman. Larry J. Eshelman 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
#WorkIndexed citations
1 8
2 4
3 59
4 13
5 27
6 6
7 11
8 27
9
Code compaction using genetic algorithms
5
10
Crossover Operator Biases: Exploiting the Population Distribution.
53
11
Proceedings of the Sixth International Conference on Genetic Algorithms : University of Pittsburgh, July 15-19, 1995
5
12
Crossover's Niche
65
13
Designing Multiplierless Digital Filters Using Genetic Algorithms
17
14
chapter Real-Coded Genetic Algorithms and Interval-Schemata
45
15
Using genetic search to exploit the emergent behavior of neural networks
5
16
On Crossover as an Evolutionarily Viable Strategy.
49
17 179
18
A study of control parameters affecting online performance of genetic algorithms for function optimizationbreakdown →
611
19
Biases in the crossover landscape
222
20
MOLE: a knowledge acquisition tool that uses its head
45

About Larry J. Eshelman

Larry J. Eshelman is a scholar working on Nephrology, Critical Care and Intensive Care Medicine and Artificial Intelligence, having authored 40 papers that have together received 2.3k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (9 papers), Metaheuristic Optimization Algorithms Research (8 papers) and Acute Kidney Injury Research (7 papers). The work is most often cited by research in Artificial Intelligence (1.4k citations), Computational Theory and Mathematics (625 citations) and Industrial and Manufacturing Engineering (176 citations). Larry J. Eshelman has collaborated with scholars based in United States, Finland and United Kingdom. Frequent co-authors include J. David Schaffer, Richard A. Caruana, Rajarshi Das, Darrell Whitley, John McDermott, Keith E. Mathias, Erina Ghosh, Ming Tan, Kianoush Kashani and Nicolas W. Chbat. Their work appears in journals such as Critical Care Medicine, Mayo Clinic Proceedings and Machine Learning.

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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