Journals in Neural networks

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Biomaterials Advances

• ISSN: 2772-9508
• 5 Year impact factor: 5.5
• Impact factor: 5.5

Formerly known as Materials Science and Engineering: C, with a 2022 IF of 7.9.Biomaterials Advances includes topics at the interface of the biomedical sciences and materials engineering. These topics include: Bioinspired and biomimetic materials for medical applicationsMaterials of biological origin for medical applicationsMaterials for "active" medical applicationsSelf-assembling and self-healing materials for medical applications"Smart" (i.e., stimulus-response) materials for medical applicationsCeramic, metallic, polymeric, and composite materials for medical applicationsMaterials for in vivo sensingMaterials for in vivo imagingMaterials for delivery of pharmacologic agents and vaccinesNovel approaches for characterizing and modeling materials for medical applicationsManuscripts on biological topics without a materials science component, or manuscripts on materials science without biological applications, will not be considered for publication in Biomaterials Advances. New submissions are first assessed for language, scope and originality (plagiarism check) and can be desk rejected before review if they need English language improvements, are out of scope or present excessive duplication with published sources.Biomaterials Advances sits within Elsevier's biomaterials science portfolio alongside Biomaterials, Materials Today Bio and Biomaterials and Biosystems. As part of the broader Materials Today family, Biomaterials Advances offers authors rigorous peer review, rapid decisions, and high visibility. We look forward to receiving your submissions!

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Cognitive Systems Research

• ISSN: 1389-0417
• 5 Year impact factor: 3
• Impact factor: 2.1

Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial.The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition.Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies. Note that the journal does not publish clinical and medical papers. We also do not publish pure machine learning papers, e.g. studies proposing variants of classifiers or pure algorithmic improvements that bear no connection to cognitive systems research in the sense above.Additionally, Cognitive Systems Research plays a special role in fostering and promoting the 'BICA Challenge' to create a real-life computational equivalent of the human mind by devoting two special issues to BICA AI (Brain-Inspired Cognitive Architectures for Artificial Intelligence) related topics each year.

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Computers & Electrical Engineering

• ISSN: 0045-7906
• 5 Year impact factor: 3.8
• Impact factor: 4

The journal Computers & Electrical Engineering provides rapid publication of topical research into the integration of computer technology and computational techniques with electrical and communication and information systems. The journal publishes papers featuring novel implementations of computers and computational techniques in areas like:Signal ProcessingPower Engineering (including renewable and green energies)Artificial Intelligence - methods and applicationsSecurityPrivacyCommunicationThe journal regularly publishes special sections covering specific topics of interest. Proposals for special sections should be submitted to the Editor-in-Chief. The list of current special sections can be found at https://www.sciencedirect.com/journal/computers-and-electrical-engineering/special-issues.Contributions should be submitted online following the guidelines in the Guide for Authors.

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Fuzzy Sets and Systems

• ISSN: 0165-0114
• 5 Year impact factor: 3.1
• Impact factor: 3.2

An International Journal in Information Science and Engineering Official Publication of the International Fuzzy Systems Association (IFSA)Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies.In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.Fuzzy set-based techniques are also an important ingredient in the development of information technologies. In the field of information processing fuzzy sets are important in clustering, data analysis and data fusion, pattern recognition and computer vision. Fuzzy rule-based modeling has been combined with other techniques such as neural nets and evolutionary computing and applied to systems and control engineering, with applications to robotics, complex process control and supervision. In thefield of information systems, fuzzy sets play a role in the development of intelligent and flexible manBmachine interfaces and the storage of imprecise linguistic information. In Artificial Intelligence various forms of knowledge representation and automated reasoning frameworks benefit from fuzzy set-based techniques, for instance in interpolative reasoning, non-monotonic reasoning, diagnosis, logic programming, constraint-directed reasoning, etc. Fuzzy expert systems have been devised for fault diagnosis,and also in medical science. In decision and organization sciences, fuzzy sets has had a great impact in preference modeling and multicriteria evaluation, and has helped bringing optimization techniques closer to the users needs. Applications can be found in many areas such as management, production research, and finance. Moreover concepts and methods of fuzzy set theory have attracted scientists in many other disciplines pertaining to human-oriented studies such as cognitive psychology and some aspects of social sciences.The scope of the journal Fuzzy Sets and Systems has expanded so as to account for all facets of the field while emphasizing its specificity as bridging the gap between the flexibility of human representations and the precision and clarity of mathematical or computerized representations, be they numerical or symbolic.The journal welcomes original and significant contributions in the area of Fuzzy Sets whether on empirical or mathematical foundations, or their applications to any domain of information technology, and more generally to any field of investigation where fuzzy sets are relevant. Applied papers demonstrating the usefulness of fuzzy methodology in practical problems are particularly welcome. Fuzzy Sets and Systems publishes high-quality research articles, surveys as well as case studies. Separate sections are Recent Literature, and the Bulletin, which offers research reports, book reviews and conference announcements and various news items. Invited review articles on topics of general interest are included and special issues are published regularly.

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Information Fusion

• ISSN: 1566-2535
• 5 Year impact factor: 16.1
• Impact factor: 14.7

An International Journal on Multi-Sensor, Multi-Source Information FusionThe journal is intended to present within a single forum all of the developments in the field of multi-sensor, multi-source, multi-process information fusion and thereby promote the synergism among the many disciplines that are contributing to its growth. The journal is the premier vehicle for disseminating information on all aspects of research and development in the field of information fusion. Articles are expected to emphasize one or more of the three facets: architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome. The journal publishes original papers, letters to the Editors and from time to time invited review articles, in all areas related to the information fusion arena including, but not limited to, the following suggested topics:• Data/Image, Feature, Decision, and Multilevel Fusion • Multi-classifier/Decision Systems • Multi-Look Temporal Fusion • Multi-Sensor, Multi-Source Fusion System Architectures • Distributed and Wireless Sensor Networks • Higher Level Fusion Topics Including Situation Awareness And Management • Multi-Sensor Management and Real-Time Applications • Adaptive And Self-Improving Fusion System Architectures • Active, Passive, And Mixed Sensor Suites • Multi-Sensor And Distributed Sensor System Design • Fusion Learning In Imperfect, Imprecise And Incomplete Environments • Intelligent Techniques For Fusion Processing • Fusion System Design And Algorithmic Issues • Fusion System Computational Resources and Demands Optimization • Special Purpose Hardware Dedicated To Fusion Applications • Mining Remotely Sensed Multi-Spectral/Hyper-Spectral Image Data Bases • Information Fusion Applications in Intrusion Detection, Network Security, Information Security and Assurance arena • Applications such as Robotics, Space, Bio-medical, Transportation, Economics, and Financial Information Systems • Real-World Issues such as Computational Demands, Real-Time Constraints in the context of Fusion systems.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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Knowledge-Based Systems

• ISSN: 0950-7051
• 5 Year impact factor: 7.4
• Impact factor: 7.2

Knowledge-based Systems is an international and interdisciplinary journal in the field of artificial intelligence. The journal will publish original, innovative and creative research results in the field, and is designed to focus on research in knowledge-based and other artificial intelligence techniques-based systems with the following objectives and capabilities: to support human prediction and decision-making through data science and computation techniques; to provide a balanced coverage of both theory and practical study in the field; and to encourage new development and implementation of knowledge-based intelligence models, methods, systems, and software tools, with applications in business, government, education, engineering and healthcare.This journal's current leading topics are but not limited to:Machine learning theory, methodology and algorithmsData science theory, methodologies and techniquesKnowledge presentation and engineeringRecommender systems and E-service personalizationIntelligent decision support systems, prediction systems and warning systemsComputational Intelligence systemsData-driven optimizationCognitive interaction and brain–computer interfaceKnowledge-based computer vision techniquesSpecial Issue InstructionsKnowledge-based Systems (KBS), an international and interdisciplinary peer-reviewed academic journal in the field of artificial intelligence, welcomes the submission of special issues on timely topics within the scope of the journal. The main objectives of the journal to organize special issues are to bring together state-of-the-art and high-quality research works, to promote key advances in the science and applications in the important field of knowledge-based systems, and to drive emerging research topics and establish flagships in the field.How to submit your Special Issue proposal:Check the selection criteria below for a KBS special issue to make sure your proposal is relevant to the journal,Write your special issue proposal in the structure given below,Submit the special issue proposal to the Editor-in-Chief (EiC),The EiC and KBS special issue assessment panel will then review your proposal and reply with their decision.Guest Editors' Duty and Special Issue Process:After a special issue proposal is accepted by the journal, a call for papers can be formally distributed. All the papers submitted to the special issue will undergo a peer review process. Guest Editors will manage the process and ensure that the reviewing standards for Knowledge-Based Systems regular issues are maintained. A Managing Guest Editor, who will be responsible for distributing submissions to the other Guest Editors, will need to be nominated. After the Guest Editors make recommendations on each paper in the special issue, the EiC will make the final decisions of acceptance for publication. After all papers to be included in the Special Issue are accepted, the Guest Editors will be responsible for either preparing an Editorial (1–2 pages in length) or writing a field survey (5–10 pages in length), which will incorporate the selected papers and related literature relevant to the topic of the special issue.Reproducibility Badge Initiative and Software PublicationReproducibility Badge Initiative (RBI) is a collaboration with Code Ocean (CO), a cloud based computational reproducibility platform that helps the community by enabling sharing of code and data as a resource for non-commercial use. CO verifies the submitted code (and data) and certifies its reproducibility. Code submission will be verified by the Code Ocean team for computational reproducibility by making sure it runs, delivers results and it is self-contained. For more information please visit this help article. Note that an accepted paper will be published independently of the CO application outcome. However, if the paper receives the Reproducibility badge, it will be given additional exposure by having an attached R Badge, and by being citable at the CO website with a DOI.We invite you to convert your open source software into an additional journal publication in Software Impacts, a multi-disciplinary open access journal. Software Impacts provides a scholarly reference to software that has been used to address a research challenge. The journal disseminates impactful and re-usable scientific software through Original Software Publications which describe the application of the software to research and the published outputs.For more information contact us at: [email protected]

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Neural Networks

• ISSN: 0893-6080
• 5 Year impact factor: 7.9
• Impact factor: 6

The Official Journal of the Asia-Pacific Neural Network Society, the International Neural Network Society & the Japanese Neural Network SocietyNeural Networks provides a forum for developing and nurturing an international community of scholars and practitioners who are interested in all aspects of neural networks, including deep learning and related approaches to artificial intelligence and machine learning. Neural Networks welcomes submissions that contribute to the full range of neural networks research, from cognitive modeling and computational neuroscience, through deep neural networks and mathematical analyses, to engineering and technological applications of systems that significantly use neural network concepts and learning techniques. This uniquely broad range facilitates the cross-fertilization of ideas between biological and technological studies and helps to foster the development of the interdisciplinary community that is interested in biologically-inspired artificial intelligence. Accordingly, the Neural Networks editorial board represents experts in fields including psychology, neurobiology, computer science, engineering, mathematics, and physics. The journal publishes articles, letters, and reviews, as well as letters to the editor, editorials, current events, and software surveys. Articles are published in one of four sections: learning systems, cognitive and neural science, mathematical and computational analysis, engineering and applications.Neural Networks is the archival journal of the world's three oldest neural modeling societies: the International Neural Network Society (INNS), the European Neural Network Society (ENNS), and the Japanese Neural Network Society (JNNS). A subscription to the journal is included with membership in each of these societies.Members of the societies listed as affiliated to the journal receive a 25% discount on Article Processing Charges when they publish an article in Neural Networks as an author - this will be detailed through the submission and production processes.International Neural Network Society (INNS) members can receive additional support with a further 25% contribution from the INNS towards their open access article processing charges for accepted papers. If you are an INNS member, please submit this web form to receive reimbursement for 25% of your open access article processing charges. You will be asked to submit a PDF copy of your acceptance and production email, as well as a Wire Transfer Form.

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Neurocomputing

• ISSN: 0925-2312
• 5 Year impact factor: 5.5
• Impact factor: 5.5

Neurocomputing publishes articles describing recent fundamental contributions in the field of neurocomputing. Neurocomputing theory, practice and applications are the essential topics being covered.NEW! Neurocomputing's Software Track allows you to expose your complete Software work to the community through a novel Publication format: the Original Software PublicationOverview:Neurocomputing welcomes theoretical contributions aimed at winning further understanding of neural networks and learning systems, including, but not restricted to, architectures, learning methods, analysis of network dynamics, theories of learning, self-organization, biological neural network modelling, sensorimotor transformations and interdisciplinary topics with artificial intelligence, artificial life, cognitive science, computational learning theory, fuzzy logic, genetic algorithms, information theory, machine learning, neurobiology and pattern recognition.Neurocomputing covers practical aspects with contributions on advances in hardware and software development environments for neurocomputing, including, but not restricted to, simulation software environments, emulation hardware architectures, models of concurrent computation, neurocomputers, and neurochips (digital, analog, optical, and biodevices).Neurocomputing reports on applications in different fields, including, but not restricted to, signal processing, speech processing, image processing, computer vision, control, robotics, optimization, scheduling, resource allocation and financial forecasting.Types of publications:Neurocomputing publishes reviews of literature about neurocomputing and affine fields.Neurocomputing reports on meetings, including, but not restricted to, conferences, workshops and seminars.NEW! The Neurocomputing Software TrackNeurocomputing Software Track publishes a new format, the Original Software Publication (OSP) to disseminate exiting and useful software in the areas of neural networks and learning systems, including, but not restricted to, architectures, learning methods, analysis of network dynamics, theories of learning, self-organization, biological neural network modelling, sensorimotor transformations and interdisciplinary topics with artificial intelligence, artificial life, cognitive science, computational learning theory, fuzzy logic, genetic algorithms, information theory, machine learning, neurobiology and pattern recognition. We encourage high-quality original software submissions which contain non-trivial contributions in the above areas related to the implementations of algorithms, toolboxes, and real systems. The software must adhere to a recognized legal license, such as OSI approved licenses.Importantly, the software will be a full peer reviewed publication that is able to capture your software updates once they are released. To fully acknowledge the author's/developers work your software will be fully citable as an Original Software Publication, archived and indexed and available as a complete online "body of work" for other researchers and practitioners to discover.See the detailed Submission instructions, and more information about the process for academically publishing your Software: here

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Pattern Recognition

• ISSN: 0031-3203
• 5 Year impact factor: 7.6
• Impact factor: 7.5

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

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Pattern Recognition Letters

• ISSN: 0167-8655
• 5 Year impact factor: 4.2
• Impact factor: 3.9

An official publication of the International Association for Pattern RecognitionPattern Recognition Letters aims at rapid publication of concise articles of a broad interest in pattern recognition. Subject areas include all the current fields of interest represented by the Technical Committees of the International Association of Pattern Recognition, and other developing themes involving learning and recognition. Examples include:• Statistical, structural, syntactic pattern recognition; • Neural networks, machine learning, data mining; • Discrete geometry, algebraic, graph-based techniques for pattern recognition; • Signal analysis, image coding and processing, shape and texture analysis; • Computer vision, robotics, remote sensing; • Document processing, text and graphics recognition, digital libraries; • Speech recognition, music analysis, multimedia systems; • Natural language analysis, information retrieval; • Biometrics, biomedical pattern analysis and information systems; • Special hardware architectures, software packages for pattern recognition.We invite contributions as research reports or commentaries.Research reports should be concise summaries of methodological inventions and findings, with strong potential of wide applications. Alternatively, they can describe significant and novel applications of an established technique that are of high reference value to the same application area and other similar areas.Commentaries can be lecture notes, subject reviews, reports on a conference, or debates on critical issues that are of wide interests.To serve the interests of a diverse readership, the introduction should provide a concise summary of the background of the work in an accepted terminology in pattern recognition, state the unique contributions, and discuss broader impacts of the work outside the immediate subject area. All contributions are reviewed on the basis of scientific merits and breadth of potential interests.

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