Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Countries citing papers authored by Lawrence Davis
Since
Specialization
Citations
This map shows the geographic impact of Lawrence Davis'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 Lawrence Davis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lawrence Davis more than expected).
This network shows the impact of papers produced by Lawrence Davis. 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 Lawrence Davis. The network helps show where Lawrence Davis may publish in the future.
Co-authorship network of co-authors of Lawrence Davis
This figure shows the co-authorship network connecting the top 25 collaborators of Lawrence Davis.
A scholar is included among the top collaborators of Lawrence Davis 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 Lawrence Davis. Lawrence Davis is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Davis, Lawrence, et al.. (2002). A Modified Classifier System Compaction Algorithm. Genetic and Evolutionary Computation Conference. 920–925.17 indexed citations
Davis, Lawrence, et al.. (1993). Shall We Repair? Genetic AlgorithmsCombinatorial Optimizationand Feasibility Constraints. international conference on Genetic algorithms. 650.47 indexed citations
6.
Davis, Lawrence, et al.. (1993). A Genetic Algorithm for Survivable Network Design. international conference on Genetic algorithms. 408–415.46 indexed citations
Kelly, James D. & Lawrence Davis. (1991). Hybridizing the Genetic Algorithm and the K Nearest Neighbors Classification Algorithm.. 377–383.74 indexed citations
9.
Kelly, James D. & Lawrence Davis. (1991). A hybrid genetic algorithm for classification. International Joint Conference on Artificial Intelligence. 645–650.95 indexed citations
10.
Davis, Lawrence. (1989). Mapping Neural Networks into Classifier Systems. international conference on Genetic algorithms. 375–378.16 indexed citations
Davis, Lawrence. (1989). Adapting operator probabilities in genetic algorithms. international conference on Genetic algorithms. 61–69.368 indexed citations
13.
Davis, Lawrence. (1988). Mapping Classifier Systems Into Neural Networks. Neural Information Processing Systems. 1. 49–56.15 indexed citations
14.
Davis, Lawrence, et al.. (1987). Genetic algorithms and communication link speed design: constraints and operators. international conference on Genetic algorithms. 257–260.22 indexed citations
15.
Davis, Lawrence, et al.. (1987). Genetic algorithms and communication link speed design: theoretical considerations. international conference on Genetic algorithms. 252–256.35 indexed citations
16.
Davis, Lawrence & Frank E. Ritter. (1987). SCHEDULE OPTIMIZATION WITH PROBABILISTIC SEARCH.. 231–236.24 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.