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.
Mathematical Principles of Fuzzy Logic
1999688 citationsVilém Novák, Irina Perfilieva et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
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Countries citing papers authored by Irina Perfilieva
Since
Specialization
Citations
This map shows the geographic impact of Irina Perfilieva'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 Irina Perfilieva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Irina Perfilieva more than expected).
Fields of papers citing papers by Irina Perfilieva
This network shows the impact of papers produced by Irina Perfilieva. 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 Irina Perfilieva. The network helps show where Irina Perfilieva may publish in the future.
Co-authorship network of co-authors of Irina Perfilieva
This figure shows the co-authorship network connecting the top 25 collaborators of Irina Perfilieva.
A scholar is included among the top collaborators of Irina Perfilieva 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 Irina Perfilieva. Irina Perfilieva is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Perfilieva, Irina & Martina Daňková. (2009). Towards F-transform of a Higher Degree. European Society for Fuzzy Logic and Technology Conference. 585–588.15 indexed citations
11.
Perfilieva, Irina. (2009). Systems of Fuzzy Relation Equations in a Space with Fuzzy Preorder. European Society for Fuzzy Logic and Technology Conference. 1601–1605.3 indexed citations
12.
Štěpnička, Martin, et al.. (2009). Time Series Analysis and Prediction Based on Fuzzy Rules and the Fuzzy Transform. European Society for Fuzzy Logic and Technology Conference. 483–488.7 indexed citations
13.
Perfilieva, Irina. (2007). Fuzzy transforms in image compression and fusion. Czech digital mathematics library. 15(1). 27–37.9 indexed citations
14.
Perfilieva, Irina. (2005). Approximating models based on fuzzy transforms. European Society for Fuzzy Logic and Technology Conference. 645–650.3 indexed citations
15.
Perfilieva, Irina, et al.. (2005). Data compression on the basis of fuzzy transforms. European Society for Fuzzy Logic and Technology Conference. 663–668.4 indexed citations
Perfilieva, Irina. (2003). Fuzzy transforms and universal approximation.. European Society for Fuzzy Logic and Technology Conference. 529–533.2 indexed citations
18.
Novák, Vilém & Irina Perfilieva. (2000). Discovering the world with fuzzy logic.103 indexed citations
19.
Novák, Vilém & Irina Perfilieva. (2000). Some consequences of Herbrand and McNaughton theorems in fuzzy logic. 271–295.4 indexed citations
20.
Perfilieva, Irina. (1999). Normal forms for fuzzy logic relations and the best approximation property.. European Society for Fuzzy Logic and Technology Conference. 39–42.3 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.