Journals in Mathematics
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.
- ISSN: 1751-570X
Nonlinear Analysis: Hybrid Systems
A journal of IFAC, the International Federation of Automatic ControlNonlinear Analysis: Hybrid Systems (NAHS) welcomes all original research papers on mathematical concepts, tools, and techniques from control theory, computer science, and applied mathematics for the modelling, analysis and design of hybrid dynamical systems, i.e., systems involving the interplay between discrete and continuous dynamic behaviors.Hybrid systems are ubiquitous in many branches of engineering and science as they can model broad ranges of dynamical systems. In particular, in cyber-physical systems, which integrate sensing, computation, control and communication (cyber) parts into physical objects and infrastructures, hybrid systems play an instrumental role. The description of the behavior of the cyber parts often calls for discrete models (automata, finite-state machines, switching logic, etc.), while the physical (thermal, mechanical, electrical, physical, biological) parts are well captured by continuous modelling formalisms (e.g., differential equations), thereby naturally resulting in hybrid system models such as (stochastic) hybrid automata, timed automata, switched systems, impulsive systems, jump-flow models, piecewise affine systems, non-smooth systems, etc. Also, many physical phenomena can often be well described by non-smooth or hybrid models, including mechanical systems with impacts and friction (walking robots), switched power converters and biological systems (e.g., firing neuron models).Hybrid systems can exhibit very rich dynamics and their analysis calls for new and strong theorical foundations to guarantee their stability, safety, functionality, and performance. The development of systematic methods for efficient and reliable design of hybrid systems is therefore a key challenge on the crossroads of control theory and computer science. It is currently of high interest to control engineers, computer scientists and mathematicians in research institutions as well as in many industrial sectors.Contribution... to Nonlinear Analysis: Hybrid Systems are invited in all areas pertaining to hybrid dynamical systems including: Modeling, modeling languages and specification;Analys... computability and complexity;Stochasti... hybrid systems;Impulsive systems;Formal verification and abstraction;Optimiza... and controller synthesis;Control over communication networks including self- and event-triggered control;Network Science and multi-agent systems;Fault diagnosis and fault-tolerant control;Simulation, implementation and tools;Safety, security, privacy, and resilience for cyber-physical systems;Planning and integrated control in dynamical systems.Contribution... on applications of hybrid dynamical systems methods are also encouraged. Fields of interest include: process and manufacturing industries, automotive and mobility systems, avionics, communication networks and networked control systems, energy and power systems, transportation networks, cyber-physical and embedded systems, (synthetic) biology and biomedical applications, life sciences, safety-critical systems, mobile and autonomous robotics, and other related areas.
- ISSN: 1468-1218
Nonlinear Analysis: Real World Applications
Nonlinear Analysis: Real World Applications welcomes all research articles of the highest quality with special emphasis on applying techniques of nonlinear analysis to model and to treat nonlinear phenomena with which nature confronts us. Coverage of applications includes any branch of science and technology such as solid and fluid mechanics, material science, mathematical biology and chemistry, control theory, and inverse problems.The aim of Nonlinear Analysis: Real World Applications is to publish articles which are predominantly devoted to employing methods and techniques from analysis, including partial differential equations, functional analysis, dynamical systems and evolution equations, calculus of variations, and bifurcations theory.Two papers per year rule All the authors and co-authors cannot submit more than two papers to this journal (including co-authored papers) within a period of twelve (12) months. If you or one of your co-authors have already submitted two papers within a period of 12 months or less, your third submission (if any) will be returned to you.Rejection due to poor English Some papers with good mathematics have been rejected from this journal due to the poor level of English within the paper. It is the responsibility of the author to ensure that the English language used is correct before submitting their paper. For authors whose first language is not English, we highly recommend that you have it checked by a native English speaker or make use of an English editing service. Elsevier also offers this (at a cost) via our Webshop (English Language Editing ).
- ISSN: 0167-6377
Operations Research Letters
Operations Research Letters (ORL) is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. ORL welcomes pure methodological papers and applied papers with firm methodological grounding. All articles are restricted to at most eight journal pages, with the option to relegate proofs and additional material to an online appendix. The main criteria for the papers to be published are quality, originality, relevance, and clarity. The journal's traditional strength is in methodology, including theory, modelling, algorithms, and computational studies. Please find below a full description of the areas covered by the journal.Area EditorsApproximation Algorithms for Combinatorial Optimization Problems Area Editor: Leah Epstein Associate Editors: M. Chrobak, K. Elbassioni, M. Feldman, J. Hurink, N. Olver, J. Sgall, J. Verschae The area covers all issues relevant to the development of efficient approximate solutions to computationally difficult problems. This includes worst case analysis or competitive analysis of approximation algorithms, and complexity results.Submissions can be articles consisting of theoretical work in the area, or articles combining significant theoretical contributions of mathematical flavor with computational investigations of heuristic approaches. Articles in the area of discrete optimization that do not belong to the scope of other areas may be submitted to this area as well.Computational Social Science Area Editor: Vianney Perchet Associate Editors: A. Drutsa, P. Mertikopoulos, R. Smorodinsky This area publishes papers focusing on data-driven procedures, either from a theoretical or an applied perspective, in operation research, games, economics and other social science. The scope includes: sample/computational complexity of mechanisms, learning in games/OR/social science, empirical solutions with AI algorithms (such as, but not limited to, deep learning techniques) of complex problems, etc. Continuous Optimization Area Editor: Hector Ramirez Associate Editors: M.F. Anjos, L.M. Briceno, D. Dadush, G. Eichfelder, D. Jiang, D. Orban, F. Schoen Papers in all fields of continuous optimization that are relevant to operations research are welcome. These areas include, but are not restricted to, linear programming, nonlinear programming (constrained or unconstrained, convex or nonconvex, smooth or nonsmooth, finite or infinite-dimensional... complementarity problems, variational inequalities, bilevel programming, and mathematical programs with equilibrium constraints. Financial Engineering Area Editor: Ning Cai Associate Editors: X. He, D. Mitchell Financial engineering utilizes methodologies of optimization, simulation, decision analysis and stochastic control to analyse the effectiveness and efficiency of financial markets. This area is interested in papers that innovate in terms of methods or that develop new models which guide financial practices. Examples include but are not limited to Fintech, financial networks, market microstructure, derivative pricing and hedging, credit and systemic risk, energy markets, portfolio selection. Game Theory Area Editor: Tristan Tomala Associate Editors: S. Beal, V. Ihele, D.W.K. Yeung, G. Zaccour This area publishes papers which use game theory to analyze operations research models or make theoretical contributions to the theory of games. The scope includes (but is not limited to): cooperative and non-cooperative games, dynamic games, mechanism and market design, algorithmic game theory, games on networks, games of incomplete information. Graphs & Networks Area Editor: Gianpaolo Oriolo Associate Editors: F. Bonomo, Y. Faenza, Z. Friggstad, L. Sanita The area seeks papers that apply, in original and insightful ways, discrete mathematics to advance the theory and practice of operations research, as well as those reporting theoretical or algorithmic advances for the area. Of particular, but not exclusive, interest are papers devoted to novel applications, telecommunications and transportation networks, graphs and web models and algorithms. Inventory and Supply Chain Optimization Area Editor: Sean Zhou Associate Editors: H. Abouee Mehrizi, A. Burnetas, X. Gong, Q. Li, J. Yang The area welcomes innovative papers focused on inventory control and supply management. Examples of topics include, but are not limited to, optimal sourcing, inventory and assortment selection, pricing and inventory optimization, capacity planning, multi-item/echelon systems, algorithms and bounds, near-optimal or asymptotic optimal solutions, and incentive design. Mixed Integer Optimization Area Editor: Marc Pfetsch Associate Editors: R. Fukasawa, L. Liberti, J.P. Vielma, G. Zambelli All submissions advancing the theory and practice of mixed integer (linear or nonlinear) programming like novel techniques and algorithmic approaches in convex relaxations, branch and cut, polyhedral combinatorics and theory driven heuristics are welcome. Case studies may be considered if they contribute to the general methodology. Operations Management Area Editor: Mahesh Nagarajan Associate Editors: L. Chu, Y. Ding, N. Golrezaei, T. Huh, R. Roet-Green, D. Saban, C. Shi, L. Zhu The OM department aims to publish short, focused high quality research in the area of operations management, broadly the field of operations research applied to management problems. We welcome papers that use a wide variety of methodologies, both descriptive as well as prescriptive in nature including optimization, applied probability, simulation, and game theory. Scheduling Area Editor: Marc Uetz Associate Editors: B. Moseley, E. Pesch, R. Van Stee We seek original and significant contributions to the analysis and solution of sequencing and scheduling problems. This includes structural and algorithmic results, in particular optimization, approximation and online algorithms, as well as game theoretic modeling. All results are welcome as long as the relevance of a problem and significance of the contribution is made compellingly clear. Stochastic Models and Data Science Area Editor: Henry LamAssociate Editors: H. Bastani, J. Dong, K. Murthy, I. Ryzhov, Y. Zhou The area seeks papers broadly on the interplay between operations research and machine learning and statistics where stochastic variability and uncertainty play a crucial role. The area values both papers that develop or utilize stochastic analysis and computation in data science problems, including but not limited to reinforcement learning, stochastic iterative algorithms for model estimation or training, probabilistic analysis of statistical and machine learning tools, sampling and Monte Carlo methods, and also papers that integrate learning or statistical techniques into stochastic modeling to enhance prediction or decision-making for a wide variety of systems. Stochastic Networks and Queues Area Editor: Harsha HonnappaAssociate Editors: E. Ozkan, W. Wang, Y. ZhaoThe area seeks papers that contribute to the modeling, analysis or innovative application of stochastic networks or queues. Work submitted should propose original models and develop novel analytical or computational methods more than incremental extensions. Examples of relevant application areas include but are not limited to supply chain management, manufacturing, financial engineering, healthcare, revenue management, service operations, telecommunications, sharing economy, online markets and public sector operations research. Application-oriented papers should demonstrate direct practical impact and have a strong methodological component as well.Stochastic Optimization and Machine Learning Area Editor: Angelos Georghiou Associate Editors: M. Bodur, M. Claus, E. Feinberg, P. Vayanos The Stochastic Optimization and Machine Learning area of Operations Research Letters solicits original articles that generate novel insights into problems that arise in optimization under uncertainty and in machine learning. The focus is broad and encompasses, among others, stochastic (dynamic) programming, (distributionally) robust optimization, data-driven optimization as well as the interface of machine learning with traditional areas of operations research. Successful submissions in this area are expected to make a clear and meaningful academic contribution, which may be through the study of new problems, models, solution techniques, performance analysis and convincing and reproducible numerical evaluations.
- ISSN: 0031-3203
Pattern Recognition
Pattern Recognition is a mature but exciting and fast developing field, which underpins developments in cognate fields such as computer vision, image processing, text and document analysis and neural networks. It is closely akin to machine learning, and also finds applications in fast emerging areas such as biometrics, bioinformatics, multimedia data analysis and most recently data science. The journal Pattern Recognition was established some 50 years ago, as the field emerged in the early years of computer science. Over the intervening years it has expanded considerably.The journal accepts papers making original contributions to the theory, methodology and application of pattern recognition in any area, provided that the context of the work is both clearly explained and grounded in the pattern recognition literature. Papers whos primary concern falls outside the pattern recognition domain and which report routine applications of it using existing or well known methods, should be directed elsewhere. The publication policy is to publish (1) new original articles that have been appropriately reviewed by competent scientific people, (2) reviews of developments in the field, and (3) pedagogical papers covering specific areas of interest in pattern recognition. Various special issues will be organized from time to time on current topics of interest to Pattern Recognition. Submitted papers should be single column, double spaced, no less than 20 and no more than 35 (40 for a review) pages long, with numbered pages.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
- ISSN: 1574-1192
Pervasive and Mobile Computing
Special Issue Proposal Note PMCJ exclusively reviews Special Issue proposal forms submitted here through the designated submission system. Proposals submitted via any other means will not be considered for review. For more information on how to prepare and submit a SI proposal please check https://www.elsevier... and Scope As envisioned by Mark Weiser as early as 1991, pervasive computing systems and services have truly become integral to our daily lives. Tremendous advancements in a multitude of technologies ranging from personalized and embedded smart devices (e.g., smartphones, sensors, wearables, IoT) to ubiquitous connectivity through wireless mobile communications and cognitive networking infrastructures, to advanced computing techniques (including mobile edge/fog/cloud, data analytics and machine learning) and user-friendly middleware services and platforms have significantly contributed to the unprecedented advances in pervasive and mobile computing.Such cutting-edge pervasive technologies and paradigms have led to the convergence of cyber-physical-human systems with applications to smart environments (e.g., smart homes and cities, smart grid, smart transportation, smart health, smart agriculture) with the goal to improve human experience and quality of life without explicit awareness of the underlying communications and computing technologies. Additionally, the huge amount of (real-time) data collected via pervasive devices coupled with advanced data analytic, machine learning and AI (Artificial Intelligence) techniques for reliable prediction and decision-making are making breakthrough research in pervasive computing and applications, such as self-driving cars, predictive maintenance in the industry 4.0 environments, mobile recommendation systems, etc.The Pervasive and Mobile Computing Journal (PMC) is a high-impact, peer-reviewed technical journal that publishes high-quality scientific articles spanning theory and practice, and covering all aspects of pervasive and mobile computing and systems. Topics include, but not limited to: Pervasive Computing and Communications Architectures and ProtocolsPervasive, Mobile and Wearable Computing Systems and ServicesCyber-Physic... Systems and Cyber-Physical-Human SystemsSmart Systems and Applications (smart homes, smart cities, smart manufacturing, smart transportation, smart grid, smart health, smart agriculture, etc.)Human-centric Intelligent SystemsCognitive ComputingTrustworthy AI in Pervasive SystemsMachine Learning and Deep Learning in Pervasive and Mobile ComputingFederated, Distributed and Embedded learning, Learning at-the-edge in Pervasive SystemsLearning on Streaming Data and Continual Learning in Pervasive and Mobile SystemsBig Data and Data Analytics in Pervasive Computing SystemsInternet of Things and Social Internet of ThingsInternet of People and Internet of VehiclesEdge, Fog, Mobile Cloud and Opportunistic Computing in Pervasive and Mobile SystemsEnabling Pervasive Communication Technologies (e.g., wireless LANs, cellular, hybrid, ad hoc and cognitive networks)Wireless Sensors Networks and RFID TechnologiesUrban Sensing and Mobile CrowdsensingParticip... and Social SensingMachine-to-Ma... and Device-to-Device CommunicationsPositi... Localization and Tracking TechnologiesActivity Recognition and TrackingContext-awar... ComputingLocation-ba... Services and ApplicationsPervasiv... Service Creation, Composition, Discovery, Management, and DeliveryHuman User Interfaces and Interaction ModelsTrust, Reliability, Security, and Privacy in Pervasive and Mobile Computing SystemsPerformance Evaluation of Pervasive and Mobile Computing Systems
- ISSN: 0378-4371
Physica A: Statistical Mechanics and its Applications
Recognized by the European Physical SocietyPhysica A: Statistical Mechanics and its Applications publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems, or the large scale, by studying the statistical properties of the microscopic or nanoscopic constituents. Applications of the concepts and techniques of statistical mechanics include: applications to physical and physiochemical systems such as solids, liquids and gases, interfaces, glasses, colloids, complex fluids, polymers, complex networks, applications to economic and social systems (e.g. socio-economic networks, financial time series, agent based models, systemic risk, market dynamics, computational social science, science of science, evolutionary game theory, cultural and political complexity), and traffic and transportation (e.g. vehicular traffic, pedestrian and evacuation dynamics, network traffic, swarms and other forms of collective transport in biology, models of intracellular transport, self-driven particles), as well as biological systems (biological signalling and noise, biological fluctuations, cellular systems and biophysics); and other interdisciplinary applications such as artificial intelligence (e.g. deep learning, genetic algorithms or links between theory of information and thermodynamics/stati... physics.).Physica A does not publish research on mathematics (e.g. statistics) or mathematical methods (e.g. solving differential equations) unless an original application to a statistical physics problem is included. Also research on fluid mechanics intended for an engineering readership as well as ordinary economic/econometric... studies falls outside the scope of Physica A .Specific subfields covered by the journal are statistical mechanics applications to:Soft matterBiological systems and systems biologyChemical systemsEconophysics and sociophysicsTraffic and transportationPhase transitionsComplex systemsDeep learning, genetic algorithms and other methods of AIBenefits 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
- ISSN: 0167-2789
Physica D: Nonlinear Phenomena
Physica D (Nonlinear Phenomena) publishes research and review articles reporting on theoretical and experimental work, techniques, and ideas that advance the understanding of nonlinear phenomena. The scope of the journal encompasses mathematical methods for nonlinear systems including: wave motion, pattern formation and collective phenomena in physical, chemical and biological systems; hydrodynamics and turbulence; integrable and Hamiltonian systems; and data-driven dynamical systems. The journal encourages submissions in established and emerging application domains, for example applications of nonlinear science to artificial intelligence, robotics, control theory, complex networks, and social and economic dynamics.
- ISSN: 1571-0645
Physics of Life Reviews
Physics of Life Reviews is an international journal appearing quarterly, that publishes review articles on physics of living systems, complex phenomena in biological systems, and related fields of artificial life, robotics, mathematical bio-semiotics, and artificial intelligent systems. This journal is a unifying force, going across the barriers between disciplines, addressing all living systems from molecules to populations and from genetics to mind and artificial systems modeling these phenomena. The journal invites reviews from actively working researchers, which are broad in scope, critical, accessible to our wide readership and addresses sometimes controversial accounts of recent progress and problems.Physics of Life Reviews intends to keep the active researcher abreast of developments on a wide range of topics by publishing timely reviews, which are more than mere literature surveys but normally less than a full monograph. Although most of the reviews will be of a specialist nature, each review should contain enough introductory material to make the main points intelligible to a non-specialist and to inspire and facilitate interdisciplinary research. "Physics" in the journal name refers to the methodology unifying all areas of physics: (1) elucidating fundamental principles, (2) developing a mathematical model, (3) making experimentally verifiable predictions. We seek reviews aspiring to this universal paradigm. The reviews should address in a clear way the most important conceptual issues in a field, review existing theories and methods with their achievements and drawbacks or difficulties versus the issues, unsolved problems addressed by a new theory, method, or approach, and why a significant progress is achieved or expected. Future research directions, remaining unsolved problems, and experimental confirmations or controversies should also be addressed.
- ISSN: 2211-6753
Spatial Statistics
Spatial Statistics publishes articles on the theory and application of spatial and spatio-temporal statistics. It favours manuscripts that present theory generated by new applications, or in which new theory is applied to an important practical case. A purely theoretical study will only rarely be accepted. Pure case studies and algorithms without methodological development are not acceptable for publication.Spatial Statistics concerns the quantitative analysis of spatial and spatio-temporal data, including their statistical dependencies, heterogeneity, accuracy and uncertainties. Methodology for spatial statistics is typically found in probability theory, stochastic modelling and mathematical statistics as well as in information and computer science. Spatial statistics is used in mapping, assessing spatial data quality, sampling design optimisation, modelling of spatial structures, and drawing of valid inference and causality from a limited set of spatio-temporal data. Application fields include:• The physical domains, e.g. environment, climate, agriculture, ecology, geosciences oceanography and remote sensing. • The social/economic domains, e.g. epidemiology, population characteristics, and disease mapping.Spatial Statistics encourages the submission of short communications and case studies in spatial statistics (i.e. manuscripts up to 3000 words presenting novel spatial statistical applications).Spatia... Statistics aims to publish reproducible science. Authors are encouraged to submit and publish data, procedures, models and methods that support your research publication. It provides facilities to interlink those with your published articles.Spatial Statistics has an open attitude towards the latest developments in data science, deep learning and geoAI, as long as a substantial statistical component is present.
- ISSN: 0167-7152
Statistics & Probability Letters
Statistics & Probability Letters adopts a novel and highly innovative approach to the publication of research findings in statistics and probability. It features concise articles, rapid publication and broad coverage of the statistics and probability literature.Statistic... & Probability Letters is a refereed journal. Articles will be limited to six journal pages (13 double-space typed pages) including references and figures. Apart from the six-page limitation, originality, quality and clarity will be the criteria for choosing the material to be published in Statistics & Probability Letters. Every attempt will be made to provide the first review of a submitted manuscript within three months of submission.The proliferation of literature and long publication delays have made it difficult for researchers and practitioners to keep up with new developments outside of, or even within, their specialization. The aim of Statistics & Probability Letters is to help to alleviate this problem. Concise communications (letters) allow readers to quickly and easily digest large amounts of material and to stay up-to-date with developments in all areas of statistics and probability.The mainstream of Letters will focus on new statistical methods, theoretical results, and innovative applications of statistics and probability to other scientific disciplines. Key results and central ideas must be presented in a clear and concise manner. These results may be part of a larger study that the author will submit at a later time as a full length paper to SPL or to another journal. Theory and methodology may be published with proofs omitted, or only sketched, but only if sufficient support material is provided so that the findings can be verified. Empirical and computational results that are of significant value will be published. We also plan to publish applications and case studies that demonstrate a novel use of existing techniques or have interesting innovative ideas about data collection, modelling or inference.