Integrated Uncertainty in Knowledge Modelling and Decision Making [electronic resource] : 7th International Symposium, IUKM 2019, Nara, Japan, March 27-29, 2019, Proceedings / edited by Hirosato Seki, Canh Hao Nguyen, Van-Nam Huynh, Masahiro Inuiguchi.
Contributor(s): Seki, Hirosato [editor.]
| Nguyen, Canh Hao [editor.] | Huynh, Van-Nam [editor.] | Inuiguchi, Masahiro [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Artificial Intelligence: 11471Publisher: Cham : Springer International Publishing : Imprint: Springer, 2019Edition: 1st ed. 2019.Description: XX, 444 p. 160 illus., 84 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030148157.Subject(s): Artificial intelligence | Machine theory | Algorithms | Data mining | Computer science -- Mathematics | Numerical analysis | Artificial Intelligence | Formal Languages and Automata Theory | Algorithms | Data Mining and Knowledge Discovery | Mathematical Applications in Computer Science | Numerical AnalysisAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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Springer Nature eBookSummary: This book constitutes the refereed proceedings of the 7th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2019, held in Nara, Japan, in March 2019. The 37 revised full papers presented were carefully reviewed and selected from 93 submissions. The papers deal with all aspects of uncertainty modelling and management and are organized in topical sections on uncertainty management and decision support; econometrics; machine learning; machine learning applications; and statistical methods.
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This book constitutes the refereed proceedings of the 7th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2019, held in Nara, Japan, in March 2019. The 37 revised full papers presented were carefully reviewed and selected from 93 submissions. The papers deal with all aspects of uncertainty modelling and management and are organized in topical sections on uncertainty management and decision support; econometrics; machine learning; machine learning applications; and statistical methods.
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