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Journal of Data-Driven Decision Support Systems is an international scientific peer-reviewed open-access journal on the data science and technology of Decision Support Systems published biannually.

JDDDSS is a research journal publishing original full-length research papers, reviews, and Letters to the Editor. The Journal is devoted to the advancement and dissemination of knowledge concerning wide scope by covering the engineering and science applications of soft computing and decision support systems.

The Journal of Data-Driven Decision Support Systems welcomes research on various topics related to soft computing and decision support systems. Some of the main areas of interest include:

  • Artificial Intelligence and its Applications in decision support systems.
  • Clinical Decision Support Systems, focusing on healthcare decision-making.
  • Data Mining techniques and their use in decision support systems.
  • Decision Support Systems in the Context of Big Data.
  • The integration of Intelligent Systems with Decision Support Systems.
  • Decision Support Systems for addressing complex engineering problems.
  • Decision Support Systems in the healthcare industry.
  • Electronic Commerce and Mobile Commerce.
  • Electronic Government and its Applications.
  • Electronic Learning and Mobile Learning for educational decision support.
  • Expert Systems and Their Role in decision support.
  • Fuzzy Systems and Neural Networks in Decision-making.
  • Hybrid Intelligent Systems Combine Neural Networks, Evolutionary Algorithms, and Fuzzy Systems.
  • The application of Industrial Engineering and Operations Research in decision support.
  • Information Systems and Services that support decision-making.
  • Intelligent Decision Support in the healthcare domain.
  • Intelligent Tutoring Systems for educational support.
  • Knowledge Management Systems and their Role in decision support.
  • Linear and Nonlinear Controllers for Decision-Making.
  • Machine Learning techniques applied to decision support.
  • Mathematical Modeling techniques and their use in decision support.
  • Modeling of Dynamic Systems for decision-making purposes.
  • Multi-Criteria Decision-Making Techniques Used in engineering problems.
  • Multi-Criteria Optimization methods for decision support.
  • Nano-Technology Modelling and its Applications.
  • Risk Management in decision-making, incorporating Soft Computing techniques.
  • System Identification and Signal Processing in decision support.
  • Soft Computing Techniques in the Context of Big Data.
  • Soft Computing techniques applied to decision support systems.
  • Soft Computing Applications in Internet Modeling, Communication, Networking, and Web Mining.
  • Soft Computing Techniques for Pattern Recognition.
  • Recommender Systems and their Integration with Soft Computing Techniques.
  • Soft Computing techniques applied to Management decisions.
  • Soft Computing Techniques in Web Information Retrieval.
  • Soft Computing Methods for Business Optimization.
  • Soft Computing techniques applied to Civil Engineering.
  • Soft Computing techniques applied to Computer Engineering.
  • Soft Computing techniques applied to Electrical Engineering.
  • Soft Computing techniques applied to Industrial Engineering.
  • Soft Computing techniques applied to Mechanical Engineering.
  • Web-based and Mobile Decision Support Systems.

These areas represent the major fields of interest for the Journal of Data-Driven Decision Support Systems and provide a comprehensive overview of the topics covered in the journal.