Artificial intelligence in models, methods and applications / Olga Dolinina, Igor Bessmertny, Alexander Brovko, Vladik Kreinovich, Vitaly Pechenkin, Alexey Lvov, Vadim Zhmud, editors.
2023
Q334 .I58 2023
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Title
Artificial intelligence in models, methods and applications / Olga Dolinina, Igor Bessmertny, Alexander Brovko, Vladik Kreinovich, Vitaly Pechenkin, Alexey Lvov, Vadim Zhmud, editors.
Meeting Name
ISBN
9783031229381 electronic book
303122938X electronic book
3031229371
9783031229374
303122938X electronic book
3031229371
9783031229374
Published
Cham : Springer, 2023.
Language
English
Description
1 online resource (694 p.).
Item Number
10.1007/978-3-031-22938-1 doi
Call Number
Q334 .I58 2023
Dewey Decimal Classification
006.3
Summary
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.
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Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed May 4, 2023).
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Series
Studies in systems, decision and control ; v. 457.
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Table of Contents
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.
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.