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Journals in Decision sciences

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Analytic Methods in Accident Research

  • ISSN: 2213-6657
  • 5 Year impact factor: 12.7
  • Impact factor: 12.9
Analytic Methods in Accident Research publishes manuscripts that deal with the development and/or application of innovative statistical and econometric methods to the study of vehicle crashes and other transportation and non-transportation-related accidents. The intent of the journal is to demonstrate how such innovative methodological approaches can be used to provide new insights and quantification of the factors that affect the frequency and severity of accidents - thus providing new guidance for the implementation of appropriate countermeasures. While the focus of the journal is on the underlying analytic approach, acceptable application areas include all elements of transportation safety (road, pedestrian, air, rail, and water safety), construction safety, and any area of study where the unintended consequences of human behavior, machine failures or system failures result in property damage and/or bodily injury.
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Artificial Intelligence in the Life Sciences

  • ISSN: 2667-3185
Providing a scientific forum for practical applications and theoretical advances of Artificial Intelligence (AI) in the life sciences and related disciplines including (but not restricted to): General, molecular, and systems biology Population and disease genetics Medicinal chemistry and chemical biology Pharmacology and drug discovery Epidemiology and clinical investigations Background: Artificial Intelligence originates from computer science and covers a wide range of approaches intended to enhance the ability of machines to make data-driven decisions and accurate predictions of events. In many scientific fields, AI is being increasingly considered and integrated, especially in the context of Big Data. Given their complexity and highly interdisciplinary nature, the life sciences provide ample opportunities for AI to impact R&D efforts in a variety of ways. Key words: Artificial Intelligence; Life Sciences; Drug Discovery; Bio- and Cheminformatics, Machine Learning; Machine Intelligence; Deep Learning; Data Mining; Big Data.
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  • ISSN: 0005-1098
  • 5 Year impact factor: 7.4
  • Impact factor: 6.4
Automatica 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 Papers should be submitted using the on-line review management system Pampus
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Communications in Transportation Research

  • ISSN: 2772-4247
Communications in Transportation Research publishes peer-reviewed high-quality research representing important advances of significance to emerging transport systems. The mission is to provide fair, fast, and expert peer review to authors and insightful theories, impactful advances, and interesting discoveries to readers. We welcome submissions of significant and general topics, of inter-disciplinary nature (transport, civil, control, artificial intelligence, social science, psychological science, medical services, etc.), of complex and inter-related system of systems, of strong evidence of data strength, of visionary analysis and forecasts towards the way forward, and of potentially implementable and utilizable policies/practices. To be more specific, the scope of expected submissions includes but is not limited to: Interactions among transportation systems and other systems Integrations of emerging technologies with transportation systems Big data analytics in transportation area Advances and discoveries in transportation area Forward-looking judgment for future transportation systems Emerging technologies/products and their impact on transportation Novel transportation modes and associated analytics Governmental initiated transportation policies and impact analysis Mobility as a service Field experiments of emerging transportation technologies Transportation electrification, automation, and connectivity Communications in Transportation Research is a fully open access journal. It is co-published by Tsinghua University Press and Elsevier, and co-sponsored by the State Key Laboratory of Automotive Safety and Energy (Tsinghua University) and China Intelligent Transportation Systems Association (ITS China). At its discretion, Tsinghua University Press will pay the open access fee for all published papers from 2021 to 2025.
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Computers & Industrial Engineering

  • ISSN: 0360-8352
  • 5 Year impact factor: 7.3
  • Impact factor: 7.9
Industrial engineering is one of the earliest fields to utilize computers in research, education, and practice. Over the years, computers and electronic communication have become an integral part of industrial engineering. Computers & Industrial Engineering (CAIE) is aimed at an audience of researchers, educators and practitioners of industrial engineering and associated fields. It publishes original contributions on the development of new computerized methodologies for solving industrial engineering problems, as well as the applications of those methodologies to problems of interest in the broad industrial engineering and associated communities. The journal encourages submissions that expand the frontiers of the fundamental theories and concepts underlying industrial engineering techniques. CAIE also serves as a venue for articles evaluating the state-of-the-art of computer applications in various industrial engineering and related topics, and research in the utilization of computers in industrial engineering education. Papers reporting on applications of industrial engineering techniques to real life problems are welcome, as long as they satisfy the criteria of originality in the choice of the problem and the tools utilized to solve it, generality of the approach for applicability to other problems, and significance of the results produced. A major aim of the journal is to foster international exchange of ideas and experiences among scholars and practitioners with shared interests all over the world. For more information, please visit the Journal's Editorial Office page. 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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Computers & Operations Research

  • ISSN: 0305-0548
  • 5 Year impact factor: 5
  • Impact factor: 4.6
Operations research and computers interact in many scientific fields of vital importance to our society. These include, among others, transportation, economics, investment strategy, inventory control, logistics, safety, reliability, urban planning, and ecology. Computers & Operations Research (COR) provides an international forum for the application of computers and operations research techniques to problems in these and related fields. The common element in all the scientific areas that this Journal addresses is the need for some optimization methodology for determining viable solutions to problems, using computers and the techniques of operations research. However, it is not only the methodology which is of interest: the applications are of equal importance. The two are mutually supportive, since understanding the application helps one greatly to comprehend the optimization methods used, and vice versa. This Journal will therefore concern itself with these scientific fields of application, and will be accordingly broad in scope of subject matter. The form, content and language of the articles will take cognizance of this breadth of applications and of the consequent fact that many readers may not be expert in the scientific field to which the computer and operations research techniques are applied by the author. All full-length research papers must contain original research results, and demonstrate constructive algorithmic complexity and extensive numerical experiments. Numerical illustrations (examples) are not sufficient: the numerical experiments must have a scientific value of their own, particularly with comparisons to other approaches. In addition, the research performed should represent novel and significant work relative to the relevant literature. The use of real-world data is also valued. (Meta)heuristics (other than well-established algorithms such as evolutionary algorithms or ant colony optimization) must be described in metaphor-free language. This is a way to ensure that they are immediately comparable to existing algorithms. Moreover, this facilitates highlighting the algorithmic contributions to the literature. Computers & Operations Research now incorporates Surveys in Operations Research and Management Science. COR will therefore also publish state-of-the-art surveys and best practice guides in analytics, operations research, and management science, in a special Surveys section. These reviews of leading research in the field enable educators, researchers and students to obtain an overview of subjects of current interest, as well as important recent developments in established areas. Submissions can focus on theory or applications of OR/MS, and can be of several types, including but not limited to: (i) Results that are considered standards by experts in the community but which have not been documented in textbooks; (ii) Standard results which have been, in some way, streamlined such as, for example, new proof techniques leading to more elegant derivations of known results; (iii) New developments in methodology, or new application areas ('hot topics'). A review should be critical with respect to the existing knowledge and should focus on the computational and algorithmic aspects/developments. For more information on writing a contribution for the Surveys section of COR, please refer to What Makes a Good Survey? Computers & Operations Research also publishes focused issues on topics of interest related to its editorial mission. Such issues typically contain between six and twelve articles. They are put together within an eighteen-month period under the responsibility of one or several guest editors. Prospective guest editors are encouraged to contact the Editor-in-Chief. Computers & Operations Research does not endorse works investigating neither warfare optimization problems nor applications involving activities that might cause serious injuries or even death, regardless of the setting (offensive or defensive). It is the responsibility of the authors to ensure that the submitted manuscripts are written using proper English, that possible grammatical or spelling errors are eliminated and that the text conforms to correct scientific English. Submissions which do not satisfy these criteria may be rejected without being sent to reviewers.
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Computers in Industry

  • ISSN: 0166-3615
  • 5 Year impact factor: 10.4
  • Impact factor: 10
The aim of Computers in Industry is to publish original, high-quality, application-oriented research papers that: • Show new trends in and options for the use of Information and Communication Technology in industry; • Link or integrate different technology fields in the broad area of computer applications for industry; • Link or integrate different application areas of ICT in industry. General topics covered include the following areas: • The unique application of ICT in business processes such as design, engineering, manufacturing, purchasing, physical distribution, production management and supply chain management. This is the main thrust of the journal. It includes research in integration of business process support, such as in enterprise modelling, ERP, EDM. • The industrial use of ICT in knowledge intensive fields such as quality control, logistics, engineering data management, and product documentation will certainly be considered. • Demonstration of enabling capabilities of new or existing technologies such as hard real time systems, knowledge engineering, applied fuzzy logic, collaborative work systems, and intelligence agents are also welcomed. • Papers solely focusing on ICT or manufacturing processes may be considered out of scope. A continuous quality policy, based on strict peer reviewing shall ensure that published articles are: - Technologically outstanding and front-end - Application-oriented with a generalised message - Representative for research at an international level 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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Decision Analytics Journal

  • ISSN: 2772-6622
Decision Analytics Journal is a forum for exchange of research findings, analysis, information, and knowledge in areas that include but are not limited to: Predictive Modelling - Decision Analytics encourages research endeavours that identify organizational risks and opportunities by exploiting patterns found in historical and transactional data. Simulation Modelling - Decision Analytics promotes application of simulation in enterprise and organizational context for examining and comparing options and scenarios prior to implementation. Optimization Modelling - Decision Analytics promotes research that can help decision-makers make the best choice by means of various optimization models. Prescriptive Methods - Decision Analytics invites research that supports the joint application of predictive models and optimization technology to create better solutions for decision-makers. Business Intelligence - Decision Analytics invites research that utilizes the latest techniques in data mining, analysis, and performance management to help decision-makers gain and sustain a competitive edge. The journal is subdivided into four Departments Descriptive Analytics Department handles manuscripts and studies answering the question of what happened by analyzing historical data and extracting hindsight about the past, without explaining why. Diagnostic Analytics Department handles manuscripts and studies answering the question of why something happened by measuring historical data against other data (i.e., benchmarks) and extracting insight into the present. Predictive Analytics Department handles manuscripts and studies answering the question of what will happen by using the findings of descriptive and diagnostic analytics and giving the foresight for the future. Prescriptive Analytics Department handles manuscripts and studies answering the question of what to do by using the findings of descriptive and diagnostic analytics and giving the prescription for the future to eliminate a problem or take advantage of a promising trend.
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Decision Support Systems

  • ISSN: 0167-9236
  • 5 Year impact factor: 8.1
  • Impact factor: 7.5
The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs). Manuscripts may draw from diverse methods and methodologies, including those from decision theory, economics, econometrics, statistics, computer supported cooperative work, data base management, linguistics, management science, mathematical modeling, operations management, cognitive science, psychology, user interface management, and others. However, a manuscript focused on direct contributions to any of these related areas should be submitted to an outlet appropriate to the specific area. Examples of research topics that would be appropriate for Decision Support Systems include the following: 1. DSS Foundations e.g. principles, concepts, and theories of enhanced decision making; formal languages and research methods enabling improvements in decision making. It is important that theory validation be carefully addressed. 2. DSS Functionality e.g. methods, tools, and techniques for developing the functional aspects of enhanced decision making; solver, model, and/or data management in DSSs; rule formulation and management in DSSs; DSS development and use in computer supported cooperative work, negotiation, research and product. 3. DSS Interfaces e.g. methods, tools, and techniques for designing and developing DSS interfaces; development, management, and presentation of knowledge in a DSS; coordination of a DSS's interface with its functionality. 4. DSS Implementation - experiences in DSS development and utilization; DSS management and updating; DSS instruction/training. A critical consideration must be how specific experiences provide more general implications. 5. DSS Evaluation and Impact e.g. evaluation metrics and processes; DSS impact on decision makers, organizational processes and performance.
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Discrete Applied Mathematics

  • ISSN: 0166-218X
  • 5 Year impact factor: 1.1
  • Impact factor: 1.1
The aim of Discrete Applied Mathematics is to bring together research papers in different areas of algorithmic and applicable discrete mathematics as well as applications of combinatorial mathematics to informatics and various areas of science and technology. Contributions presented to the journal can be research papers, short notes, surveys, and possibly research problems. The "Communications" section will be devoted to the fastest possible publication of recent research results that are checked and recommended for publication by a member of the Editorial Board. The journal will also publish a limited number of book announcements as well as proceedings of conferences. These proceedings will be fully refereed and adhere to the normal standards of the journal. Potential authors are advised to view the journal and the open calls-for-papers of special issues before submitting their manuscripts. Only high-quality, original work that is within the scope of the journal or the targeted special issue will be considered. 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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