Algorithms in Decision Support Systems

• Autore: García-Díaz Vicente
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
• Descrizione fisica: 1 online resource (162 p.)
• Soggetto topico: History of engineering and technology
• Soggetto non controllato: algorithm evaluation; associative classification; big data; Boolean logic; class association rule; classification; component-based approach; computational methods list; computer algebra systems; data envelopment analysis; decision support systems; deep learning; dimensionality reduction; Eclipse-RCP (Rich Client Platform); ensembles; entropy; exhaustive state space search; external sources; geographically dispersed systems; Groebner bases; indicators list; interactive platform; machine learning; meta-database; multi-objective optimization; Nonlinear regression; parallel algorithms; personalized patient care; population health management; radar emitter; rule-based expert systems; semi-supervised learning; software architecture; spatial prediction; teleological meta-database; tennis hitting technique; thematic list; train rescheduling; transfer learning; vertical data representation; very large-scale data and program cores of information systems; very large-scale decision support systems
• 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