Expert Systems With Applications is a refereed international journal whose focus is on exchanging information relating to expert and intelligent systems applied in industry, government, and universities worldwide. The thrust of the journal is to publish original papers dealing with the design, development, testing, implementation, and/or management of expert and intelligent systems, and also to provide practical guidelines in the development and management of these systems. The journal will publish papers in expert and intelligent systems technology and application in the areas of, but not limited to: finance, accounting, engineering, marketing, auditing, law, procurement and contracting, project management, risk assessment, information management, information retrieval, crisis management, stock trading, strategic management, network management, telecommunications, space education, intelligent front ends, intelligent database management systems, medicine, chemistry, human resources management, human capital, business, production management, archaeology, economics and energy. Papers in multi-agent systems, knowledge management, neural networks, knowledge discovery, data and text mining, multimedia mining, and genetic algorithms will also be published in the journal. The journal no longer considers papers that contain applications to military/defense systems.
Papers detailing algorithms which repurpose existing concepts within the framework of metaphors inspired by various systems and processes, such as natural, technical, or social ones are discouraged as this can hinder effective algorithm comparisons and scientific advancement. Submissions from this field are required to convincingly demonstrate their contribution to the field in order to be considered for further evaluation. Authors are urged to present their methods with clarity, employing standard optimization terminology, and to provide compelling explanations for how their components are adapted to specific problem-solving contexts. The emphasis is on genuine innovation rather than the renaming of existing concepts.
Natural metaphor articles - new nature-inspired proposals detailed in papers must provide formal, mathematically grounded explanations for how they differ from established methods and the use of metaphors as superficial embellishments is discouraged.
Reproducibility Badge Initiative and Software Publication
Reproducibility 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.
Expert Systems With Applications is a refereed international journal whose focus is on exchanging information relating to expert and intelligent systems applied in industry, government, and universities worldwide. The thrust of the journal is to publish original papers dealing with the design, …
Machine Learning with Applications (MLWA) is a peer reviewed, open access journal focused on research related to machine learning. The journal encompasses all aspects of research and development in ML, including but not limited to data mining, computer vision, natural language processing (NLP), …
