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Journals in Mathematics

The Mathematics collection presents a range of foundational and advanced research content across applied and discrete mathematics, including fields such as Computational Mathematics; Differential Equations; Linear Algebra; Modelling & Simulation; Numerical Analysis; Probability & Statistics.

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Automatica

  • ISSN: 0005-1098
  • 5 Year impact factor: 6
  • Impact factor: 4.8
A Journal of IFAC, the International Federation of Automatic ControlAutomatica is a leading archival publication in the field of systems and control. The field encompasses today a broad set of areas and topics, and is thriving not only within itself but also in terms of its impact on other fields, such as communications, computers, biology, energy and economics. Since its inception in 1963, Automatica has kept abreast with the evolution of the field over the years, and has emerged as a leading publication driving the trends in the field.After being founded in 1963, Automatica became a journal of the International Federation of Automatic Control (IFAC) in 1969. It features a characteristic blend of theoretical and applied papers of archival, lasting value, reporting cutting edge research results by authors across the globe. It features articles in distinct categories, including regular, brief and survey papers, technical communiqués, correspondence items, as well as reviews on published books of interest to the readership. It occasionally publishes special issues on emerging new topics or established mature topics of interest to a broad audience.Automatica solicits original high-quality contributions in all the categories listed above, and in all areas of systems and control interpreted in a broad sense and evolving constantly. They may be submitted directly to a subject editor or to the Editor-in-Chief if not sure about the subject area. Editorial procedures in place assure careful, fair, and prompt handling of all submitted articles. Accepted papers appear in the journal in the shortest time feasible given production time constraints.Additional information about Automatica, including a list of recently accepted papers and a cumulative table of contents (1963-present), can be found at the website www.journals.elsevier.com/automatica. Papers should be submitted using the on-line review management system Pampus www.autsubmit.com.
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Automatica

Big Data Research

  • ISSN: 2214-5796
  • 5 Year impact factor: 3.5
  • Impact factor: 3.5
The journal aims to promote and communicate advances in big data research by providing a fast and high quality forum for researchers, practitioners and policy makers from the very many different communities working on, and with, this topic.The journal will accept papers on foundational aspects in dealing with big data, as well as papers on specific Platforms and Technologies used to deal with big data. To promote Data Science and interdisciplinary collaboration between fields, and to showcase the benefits of data driven research, papers demonstrating applications of big data in domains as diverse as Geoscience, Social Web, Finance, e-Commerce, Health Care, Environment and Climate, Physics and Astronomy, Chemistry, life sciences and drug discovery, digital libraries and scientific publications, security and government will also be considered. Occasionally the journal may publish whitepapers on policies, standards and best practices.Benefits to authorsWe also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services .Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center.
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Big Data Research

BioSystems

  • ISSN: 0303-2647
  • 5 Year impact factor: 1.8
  • Impact factor: 2
BioSystems encourages theoretical, computational and experimental articles that link biology, evolutionary concepts, and the information processing sciences. The journal is dedicated to developing the consequences of the discoveries of biological information and of the genetic code - with the view of obtaining a better understanding of the origins and evolution of biological organization, biological adaptability, and the origin of mind and language.The scope of the journal encompasses the fundamental nature of biological information processing. This includes quantum phenomena in information transfer, natural computing, biological coding systems, biological complexity, theoretical biology, artificial life, computational modeling of complex biological systems, evolutionary models of computation, application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.The journal does not publish purely medical, computational, or ecological research, unless it is clearly linked to the basic and conceptual aspects of biological organization.The editors encourage articles that deal, in particular, with the following topics: Biological computationMolecular recognitionPhysical foundations of biologyQuantum phenomena in biological systemsCellular controlNeuromolecular computingBiological coding systemsMolecular computing processesSelf-organizing and self-replicating systemsOrigins and evolution of the genetic mechanismStochastic evolutionary algorithmsOrigins and evolution of mind and languageSimulation of genetic and ecological systemsApplications (neural nets, machine learning, robotics)In addition, the editors encourage the following types of papers for submission: Papers that extract novel biological insights from multidimensional data using AI-driven language modelsBiological hypothesis papers producing new insights based on a body of pre-existing empirical research
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BioSystems

Bulletin des Sciences Mathématiques

  • ISSN: 0007-4497
  • 5 Year impact factor: 1.1
  • Impact factor: 1.3
Articles in French and English For more information on our journals visit: https://www.elsevier.com/mathematicsFounded in 1870, by Gaston Darboux, the Bulletin publishes original articles covering all branches of pure mathematics. During the last few years the Bulletin has published contributions by T. Aubin, H. Bauer, R. Beals, L. De Branges, L. Carleson, A. Chang, G. Choquet, J. Dixmier, J.P. Demailly, L. Ehrenpreis, P. Erdös, B. Gaveau, P. Greiner, A. Koranyi, T. Levasseur, P. Malliavin, H. Moscovici, O.G. Pisier, H. Rosenberg, E. Stein, M. Talagrand, A. Tognoli, A. Varchenko, N. Varopoulos, A. Weinstein, H. Widom, M. Yor.Benefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission.This journal has an Open Archive. All published items, including research articles, have unrestricted access and will remain permanently free to read and download 48 months after publication. All papers in the Archive are subject to Elsevier's user license.If you require any further information or help, please visit our Support Center
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Bulletin des Sciences Mathématiques

Chaos, Solitons & Fractals

  • ISSN: 0960-0779
  • 5 Year impact factor: 5.4
  • Impact factor: 5.3
An interdisciplinary journal of nonlinear scienceChaos, Solitons & Fractals has an open access companion journal Chaos, Solitons & Fractals: X which has the same aims and scope, editorial board and peer-review process. .Chaos, Solitons & Fractals aims to be the leading journal in the interdisciplinary field of Nonlinear Science.It encourages the submission of high-quality articles (under the form of short communications, regular papers, and review papers) containing results which have a significant impact on the following subjects:nonlinear dynamics and non-equilibrium processes in physics and applied mathematics;complex matter and networks;biophysics, systems biology and computational biology;fluctuations and random processes;artificial intelligence, machine learning and big data analytics;self-organization and emergent phenomena;applications to social science, engineering and econophysics.The journal can only accept papers whose primary subject area lies within the above Aims & Scope.In particular, please take notice of the following, additional, criteria:In order to be acceptable, manuscripts of more mathematical nature should have a clear and explicit connection to physical insight or new qualitative features. The word "Solitons" should be understood as a label especially extended to all nonlinear integrable systems in complex natural phenomena. The paper should not bear on some explicit formulae, some standard solutions, constructions, or asymptotic methods.The journal is interested in articles providing strong insights in the mathematical theory of fractals that are profound for an important particular application, especially in complex systems. Numerical computations should only assist the developed results.The submitted Manuscripts should contain presentations which are a) of interdisciplinary interest, b) easily accessible also to a non-specialized-audience, and c) written in an excellent English style.Notice that if the above criteria are not fulfilled, submissions may be desk-rejected by the Journal's Editors without being sent to reviewers.
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Chaos, Solitons & Fractals

Communications in Nonlinear Science and Numerical Simulation

  • ISSN: 1007-5704
  • 5 Year impact factor: 3.3
  • Impact factor: 3.4
Aims:The journal publishes original research findings on experimental observation, mathematical modeling, theoretical analysis and numerical simulation, for more accurate description, better prediction or novel application, of nonlinear phenomena in science and engineering. It offers a venue for researchers to make rapid exchange of ideas and techniques in nonlinear science.The submission of manuscripts with cross-disciplinary approaches in nonlinear science is particularly encouraged.Topics of interest:High-dimensional Chaos, Turbulence (fluid mechanics, plasma physics, magnetohydrodynamics, nonlinear internal and surface waves, pattern formation and selection, non-Newtonian fluid flows)Hamiltonian Systems and Applications (atomic and molecular physics, accelerator physics, chemical physics, celestial mechanics and astronomy, plasma physics)Time-Series and Signal Analysis, Experimental Methods and Measurements (methods for signal analysis, models in economics and finance, laboratory experiments)Biological Physics (ecology and environmental science, climate modeling, bioengineering, biomechanics, biological data, neuronal systems, cardiac dynamics, haemodynamics, epidemic models and dynamics of infectious diseases, experimental and theoretical analysis in life sciences)Complexity and Networks (neural networks, complex network, engineering oriented complex systems, artificial intelligence and machine learning, sociophysics)Synchronization, Lyapunov Analysis and Control (Lyapunov theory in dynamical systems, synchronization in complex systems, optimization and control)Nonlinear Mechanical Systems (MEMS and NEMS devices, continuous mechanics of solids, robotics, viscoelasticity and plasticity, energy production, conversion and storage, acoustics, nonlinear vibrations, nonlinear acoustics, porous media, granular matter)Bifurcations, Attractors and ChaosComputational Methods (modeling, analysis and simulations, numerical methods for ordinary and partial differential equations, symbolic computational methods)Analytical Methods (exact solutions for nonlinear differential equations, asymptotic methods in nonlinear dynamics, Lie group analysis, integrable systems and solitons, symbolic dynamics)Discrete, Stochastic and Hybrid Dynamics (discontinuous dynamical systems, hybrid systems, stochastic processes)Fractional Dynamics (fractional dynamics and control, fractional calculus)No length limitation for contributions is set, but only concisely written manuscripts are published. Brief papers are published on the basis of Short Communications. Discussions of previously published papers are welcome.Benefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center
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Communications in Nonlinear Science and Numerical Simulation

Computational Geometry

  • ISSN: 0925-7721
  • 5 Year impact factor: 0.5
  • Impact factor: 0.4
Theory and ApplicationsComputational Geometry is a forum for research in theoretical and applied aspects of computational geometry. The journal publishes fundamental research in all areas of the subject, as well as disseminating information on the applications, techniques, and use of computational geometry. Computational Geometry publishes articles on the design and analysis of geometric algorithms. All aspects of computational geometry are covered, including the numerical, graph theoretical, combinatorial and computational topology aspects. Also welcomed are computational geometry solutions to fundamental problems arising in computer graphics, pattern recognition, robotics, image processing, CAD-CAM, VLSI design and geographical information systems.Computational Geometry features a special section containing open problems and concise reports on implementations of computational geometry tools.Benefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center
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Computational Geometry

Computational Statistics & Data Analysis

  • ISSN: 0167-9473
  • 5 Year impact factor: 1.7
  • Impact factor: 1.5
The Official Journal of the Network Computational and Methodological Statistics (CMStatistics) and the International Association of Statistical Computing (IASC)Computational Statistics and Data Analysis (CSDA), an Official Publication of the network Computational and Methodological Statistics (CMStatistics) and of the International Association for Statistical Computing (IASC), is an international journal dedicated to the dissemination of methodological research and applications in the areas of computational statistics and data analysis. The journal consists of four refereed sections which are divided into the following subject areas:I) Computational Statistics - Manuscripts dealing with:the explicit impact of computers on statistical methodology (e.g., Bayesian computing, bioinformatics, computer graphics, computer intensive inferential methods, data exploration, data mining, expert systems, heuristics, knowledge based systems, machine learning, neural networks, numerical and optimization methods, parallel computing, statistical databases, statistical systems), the development, evaluation and validation of statistical software and algorithms. Software and algorithms can be submitted with manuscripts and will be stored together with the online article.II) Statistical Methodology for Data Analysis - Manuscripts dealing with: novel and original data analytical strategies and methodologies applied in biostatistics (design and analytic methods for clinical trials, epidemiological studies, statistical genetics, or genetic/environmental interactions), chemometrics, classification, data exploration, density estimation, design of experiments, environmetrics, education, image analysis, marketing, model free data exploration, pattern recognition, psychometrics, statistical physics, image processing, robust procedures. Statistical methodology includes, but not limited to: bootstrapping, classification techniques, clinical trials, data exploration, density estimation, design of experiments, pattern recognition/image analysis, parametric and nonparametric methods, statistical genetics, Bayesian modeling, outlier detection, robust procedures, cross-validation, functional data, fuzzy statistical analysis, mixture models, model selection and assessment, nonlinear models, partial least squares, latent variable models, structural equation models, supervised learning, signal extraction and filtering, time-series modelling, longitudinal analysis, multilevel analysis and quality control.III) Special Applications - Manuscripts at the interface of statistics and computing (e.g., comparison of statistical methodologies, computer-assisted instruction for statistics, simulation experiments). Advanced statistical analysis with real applications (social sciences, marketing, psychometrics, chemometrics, signal processing, medical statistics, environmentrics, statistical physics).IV) Statistical Data Science - The manuscripts concern with well-founded theoretical and applied data-driven research, with a significant computational or statistical methodological component for data analytics. Emphasis is given to comprehensive and reproducible research, including data-driven methodology, algorithms and software. This journal section serves as a complementary component to the network Computational and Methodological Statistics (CMStatistics).
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Computational Statistics & Data Analysis

Computer Methods in Applied Mechanics and Engineering

  • ISSN: 0045-7825
  • 5 Year impact factor: 6.7
  • Impact factor: 6.9
The development of computational methods for the solution of scientific and engineering problems governed by the laws of mechanics was one of the great scientific and engineering achievements of the second half of the 20th century, with a profound impact on science and technology. This is accomplished through advanced mathematical modeling and numerical solutions reflecting a combination of concepts, methods and principles that are often interdisciplinary in nature and span several areas of mechanics, mathematics, computer science and other scientific disciplines as well.Computer Methods in Applied Mechanics and Engineering was founded over five decades ago, providing a platform for the publication of papers in this important field of computational science and engineering. The range of appropriate contributions is very wide. It covers any type of computational method for the simulation of complex physical problems leading to the analysis and design of engineering products and systems. This includes theoretical development and rational applications of mathematical models, variational formulations, and numerical algorithms related to finite element, boundary element, finite difference, finite volume, isogeometric and meshless discretization methods in the following fields of of simulation-based engineering science:• Solid and structural mechanics • Fluid mechanics • Mechanics of materials • Heat transfer • Dynamics • Geomechanics • Acoustics • Biomechanics • Nanomechanics • Molecular dynamics • Quantum mechanics • Electromagneticsand also includes virtual design, multiscale phenomena, from nanoscale to macroscale, multiphysics problems, parallel computing, optimization, machine learning, probabilistic and stochastic approaches.CMAME publishes original papers at the forefront of modern research describing significant developments of computational methods in solving problems of applied mechanics and engineering.
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Computer Methods in Applied Mechanics and Engineering

Computer Science Review

  • ISSN: 1574-0137
  • 5 Year impact factor: 13.3
  • Impact factor: 13.3
Computer Science Review publishes research surveys and expository overviews of open problems in computer science.All articles are aimed at a general computer science audience seeking a full and expert overview of the latest developments across computer science research.Articles from other fields are welcome, as long as their content is relevant to and has impact on the development of computer science. In particular, articles that review the application of well-known Computer Science methods to other areas are in scope only if these articles advance the fundamental understanding of those methods.Contributing authors are expected to be recognized experts in the areas that they survey, have a significant publication record in the specific domain and the experience to provide a clear and well-balanced treatment of the subject.
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Computer Science Review

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