World's Best Scientists 2026 revealed!
Natural Computing
H-index 14

Natural Computing

1567-7818

Published by: Springer

https://www.springer.com/journal/11047

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 455 49 58 13

Additional Metrics

Number of Best Scientists*: 59
Documents by Best Scientists*: 69
Top 100 Ranked Scientists*: 2
SCIMAGO H-index: 50
SCIMAGO SJR: 0.456
Impact Factor: 1.6

Overview

Top Research Topics at Natural Computing?

Theory of computation, Complex system, Artificial intelligence, Algorithm and Theoretical computer science are the subjects of interest in the journal. Issues in Theory of computation were discussed, taking into consideration concepts from other disciplines like Discrete mathematics, Evolutionary algorithm, Mathematical optimization, Computation and Cellular automaton. The concepts on Artificial intelligence presented in it can also apply to other research fields, including Machine learning and Pattern recognition.

  • Theory of computation (22.81%)
  • Complex system (13.62%)
  • Artificial intelligence (12.33%)

What are the most cited papers published in the journal?

  • Evolution strategies –A comprehensive introduction (1843 citations)
  • Recent approaches to global optimization problems through Particle Swarm Optimization (1252 citations)
  • BGSA: binary gravitational search algorithm (495 citations)

Research areas of the most cited articles at Natural Computing:

The most cited publications are organized to reinforce research efforts on Theory of computation, Complex system, Artificial intelligence, Mathematical optimization and Algorithm. The journal articles facilitate discussions on Theory of computation that incorporate concepts from other fields like Discrete mathematics, Theoretical computer science, Membrane computing and Computation, DNA computing. The most cited publications address concerns in the field of Artificial intelligence by exploring it in line with topics in Field (computer science) which intersect with Management science subjects.

What topics the last edition of the journal is best known for?

  • Artificial intelligence
  • Quantum mechanics
  • Algorithm

The previous edition focused in particular on these issues:

The journal covers a variety of subjects, including Theory of computation, Complex system, Evolutionary algorithm, Theoretical computer science and Mathematical optimization. It covers Theory of computation research under the subject of Algorithm. Topics in Complex system explored in it were investigated in conjunction with research in Discrete mathematics, Topology, Set (abstract data type), Physical system and Cellular automaton.

Optimization problem, Local search (optimization) and Operator (computer programming) are some topics wherein Evolutionary algorithm research discussed in it have an impact. The journal covers various topics on Mathematical optimization such as Particle swarm optimization, Metaheuristic and Heuristic (computer science). Artificial intelligence research featured in Natural Computing incorporates concerns from various other topics such as Machine learning and Pattern recognition.

The most cited articles from the last journal are:

  • A novel hybrid BPSO–SCA approach for feature selection (8 citations)
  • Adaptive CCR-ELM with variable-length brain storm optimization algorithm for class-imbalance learning (7 citations)
  • Similarity in metaheuristics: a gentle step towards a comparison methodology (5 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in Natural Computing (based on the number of publications) are:

  • 真人 岡田 (62 papers) absent at the last edition,
  • 利通 斎藤 (34 papers) absent at the last edition,
  • 賢治 銅谷 (25 papers) absent at the last edition,
  • 和司 池田 (24 papers) absent at the last edition,
  • 徹生 古川 (23 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in Natural Computing (based on the number of publications) are:

  • University of Milan (26 papers) absent at the last edition,
  • University of Pelita Harapan (22 papers) published 7 papers at the last edition, 1 more than at the previous edition,
  • University of York (17 papers) published 3 papers at the last edition,
  • University of Seville (15 papers) absent at the last edition,
  • California Institute of Technology (14 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 24.69% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 16.39% were posted by at least one author from the top 10 institutions publishing in the journal. Another 8.20% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 4.92% of all publications and 70.49% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

How to Get Involved in Natural Computing Research

If this article piqued your interest in natural computing research, you may be wondering how to start getting involved. Regardless of your current qualifications or experience, there are a range of opportunities available for those passionate about this field. Firstly, gaining a solid foundation in related academic fields such as computer science, data science or mathematics is beneficial. For aspiring contributors in Rhode Island who currently work in education, they might be pondering, [do private school teachers need a degree in Rhode Island]. While different pathways exist to becoming a private school teacher or lecturer in computer science related subjects in Rhode Island, holding a relevant degree typically affords greater opportunities for involvement in natural computing research at an academic level. Secondly, regularly reading and analyzing articles and papers published in respected scientific journals, such as the ones referenced in this piece, helps prospective researchers stay up-to-date with the latest topics and trends in natural computing. Finally, consider collaborating with established researchers or finding mentorship opportunities. These experiences could offer invaluable guidance and practical experience in natural computing research. By taking these steps towards engaging with the natural computing research field, you challenge and expand your knowledge, potentially leading to making your own valuable contributions to this intricate and ever-evolving discipline.

Top Publications

  • Similarity in metaheuristics: a gentle step towards a comparison methodology

    Jesica de Armas;Eduardo Lalla-Ruiz;Surafel Luleseged Tilahun;Stefan Voß

    (2021)
    53 Citations
  • A proposal for tuning the $$lpha $$ α parameter in $$C_{lpha }C$$ C α C -integrals for application in fuzzy rule-based classification systems

    Giancarlo Lucca;José Antonio Sanz;Graçaliz Pereira Dimuro;Graçaliz Pereira Dimuro;Benjamín R. C. Bedregal

    (2020)
    39 Citations
  • Adaptive CCR-ELM with variable-length brain storm optimization algorithm for class-imbalance learning

    Jian Cheng;Jingjing Chen;Yi-nan Guo;Shi Cheng

    (2021)
    29 Citations
  • Reservoir computing quality: connectivity and topology

    Matthew Dale;Simon O'Keefe;Angelika Sebald;Susan Stepney

    (2021)
    29 Citations
  • Perception of cloth in assistive robotic manipulation tasks

    Pablo Jiménez;Carme Torras

    (2020)
    25 Citations
  • From electric circuits to chemical networks

    Luca Cardelli;Mirco Tribastone;Max Tschaikowski

    (2020)
    25 Citations
  • Approximate majority analyses using tri-molecular chemical reaction networks

    Anne Condon;Monir Hajiaghayi;David Kirkpatrick;Ján Maňuch

    (2020)
    23 Citations
  • Spiking neural P systems: main ideas and results

    (2022)
    21 Citations
  • Evolutionary algorithms and submodular functions: benefits of heavy-tailed mutations

    Francesco Quinzan;Andreas Göbel;Markus Wagner;Tobias Friedrich

    (2021)
    20 Citations
  • Forming tile shapes with simple robots

    Robert Gmyr;Kristian Hinnenthal;Irina Kostitsyna;Fabian Kuhn

    (2020)
    19 Citations

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Best Scientists Contributing to This Journal