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Artificial Intelligence in Models, Methods and Applications 2023 ed. [Hardback]

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  • Formāts: Hardback, 712 pages, height x width: 235x155 mm, weight: 1382 g, 173 Illustrations, color; 126 Illustrations, black and white; XV, 712 p. 299 illus., 173 illus. in color., 1 Hardback
  • Sērija : Studies in Systems, Decision and Control 457
  • Izdošanas datums: 25-Apr-2023
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031229371
  • ISBN-13: 9783031229374
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  • Hardback
  • Cena: 225,41 €*
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Artificial Intelligence in Models, Methods and Applications 2023 ed.Palielināt
  • Formāts: Hardback, 712 pages, height x width: 235x155 mm, weight: 1382 g, 173 Illustrations, color; 126 Illustrations, black and white; XV, 712 p. 299 illus., 173 illus. in color., 1 Hardback
  • Sērija : Studies in Systems, Decision and Control 457
  • Izdošanas datums: 25-Apr-2023
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031229371
  • ISBN-13: 9783031229374
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783031229374.html
Keywords:
This book is based on the accepted research papers presented in the International Conference "Artificial Intelligence in Engineering & Science" (AIES-2022). The aim of the AIES Conference is to bring together researchers involved in the theory of computational intelligence, knowledge engineering, fuzzy systems, soft computing, machine learning and related areas and applications in engineering, bioinformatics, industry, medicine, energy, smart city, social spheres and other areas. This book presents new perspective research results: models, methods, algorithms and applications in the field of Artificial Intelligence (AI). Particular emphasis is given to the medical applications - medical images recognition, development of the expert systems which could be interesting for the AI researchers as well for the physicians looking for the new ideas in medicine. The central audience of the book are researchers, industrial practitioners, students specialized in the Artificial Intelligence.

Chapter 1: Semantic Modeling of Predicate Calculus Based on N-Tuple
Algebra.
Chapter 2: Method of Iterative-Order Optimization of Multicriteria
Problems Using the Local Importance of Criteria.
Chapter 3: Neural Network
Representation for Ordinary Differential Equations.
Chapter 4: Modeling
Situations in Spatial Analysis.