Algorithms in Decision Support Systems

Dear Colleagues,

Decision support systems (DSSs) are increasingly important information systems that help to make decisions related to unstructured and semi-unstructured decision problems that do not have a simple solution from a human point of view. They are currently used in different areas, such as medical diagnosis, catastrophe avoidance, agriculture, sustainable development, sales projections, inventory organization, production design, etc. The arquitecture of a common DSS is basically composed of three main components: (1) knowledge base; (2) user interface; and (3) model to infer the decisions. Such models may be based on multiple types of algorithms, such as neural networks, logistic regression, classification trees, fuzzy logic, etc. Although there are multiple works that try to optimize the operation of DSSs, researchers are still trying to optimize their performance by refining and proposing new algorithms that normally are adapted to the set of data available for a particular domain of knowledge. Thus, the aim of this Special Issue is to enhance the state-of-the-art in this area significantly, improving the performance of DSSs in specific domains. We encourage authors across the world to submit their original and unpublished works. We have a special interest in works focusing on the topics listed below, but we are open to other works that fit the theme of the Special Issue.

Dr. Vicente García-Díaz
Guest Editor

Manuscript Submission Information

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