Algorithms in Decision Support Systems

• Autore: García-Díaz Vicente
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
• Descrizione fisica: 1 electronic resource (162 p.)
• Soggetto topico: History of engineering & technology
• Soggetto non controllato: semi-supervised learning; transfer learning; radar emitter; decision support systems; population health management; big data; machine learning; deep learning; personalized patient care; Nonlinear regression; interactive platform; component-based approach; software architecture; Eclipse-RCP (Rich Client Platform); spatial prediction; rule-based expert systems; tennis hitting technique; computer algebra systems; Groebner bases; Boolean logic; data envelopment analysis; dimensionality reduction; ensembles; exhaustive state space search; entropy; associative classification; class association rule; vertical data representation; classification; algorithm evaluation; parallel algorithms; multi-objective optimization; train rescheduling; very large-scale decision support systems; very large-scale data and program cores of information systems; meta-database; teleological meta-database; thematic list; indicators list; computational methods list; geographically dispersed systems; external sources
• Persona (resp. second.): García-DíazVicente
• Sommario/riassunto: This book aims to provide a new vision of how algorithms are the core of decision support systems (DSSs), which 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. It begins with a discussion of how DSSs will be vital to improving the health of the population. The following article deals with how DSSs can be applied to improve the performance of people doing a specific task, like playing tennis. It continues with a work in which authors apply DSSs to insect pest management, together with an interactive platform for fitting data and carrying out spatial visualization. The next article improves how to reschedule trains whenever disturbances occur, together with an evaluation framework. The final works focus on different relevant areas of DSSs: 1) a comparison of ensemble and dimensionality reduction models based on an entropy criterion; 2) a radar emitter identification method based on semi-supervised and transfer learning; 3) design limitations, errors, and hazards in creating very large-scale DSSs; and 4) efficient rule generation for associative classification. We hope you enjoy all the contents in the book.
• Titolo autorizzato: Algorithms in Decision Support Systems
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557109603321
• Lo trovi qui: Univ. Federico II