Kovalev / Panov / Kuznetsov | Artificial Intelligence | Buch | 978-3-030-86854-3 | sack.de

Buch, Englisch, Band 12948, 382 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 598 g

Reihe: Lecture Notes in Computer Science

Kovalev / Panov / Kuznetsov

Artificial Intelligence

19th Russian Conference, RCAI 2021, Taganrog, Russia, October 11-16, 2021, Proceedings
1. Auflage 2021
ISBN: 978-3-030-86854-3
Verlag: Springer Nature Switzerland

19th Russian Conference, RCAI 2021, Taganrog, Russia, October 11-16, 2021, Proceedings

Buch, Englisch, Band 12948, 382 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 598 g

Reihe: Lecture Notes in Computer Science

ISBN: 978-3-030-86854-3
Verlag: Springer Nature Switzerland


This book constitutes the proceedings of the 19th Russian Conference on Artificial Intelligence, RCAI 2021, held in Moscow, Russia, in October 2021.

The 19 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 80 submissions. The conference deals with a wide range of topics, categorized into the following topical headings: cognitive research; data mining, machine learning, classification; knowledge engineering; multi-agent systems and robotics; natural language processing; fuzzy models and soft computer; intelligent systems; and tools for designing intelligent systems.

Kovalev / Panov / Kuznetsov Artificial Intelligence jetzt bestellen!

Zielgruppe


Research

Weitere Infos & Material


Cognitive Research.- Heterogeneous Formal Neurons and Modeling of Multi-Transmitter Neural Ensembles.- Methods for Recognition of Frustration-Derived Reactions in Social Media.- Identification of the Network State Based on the ART-2 Neural Network with a Hierarchical Memory Structure in Parallel Mode.- Data Mining, Machine Learning, Classification.-  Ranking Weibull Survival Model: Boosting Concordance Index of Weibull Time-to-event Prediction Model with Ranking Losses.- Predicting Different Health and Lifestyle Behaviors of Social Media Users.- Methods for Finding Consequences with Specified Properties.- Data Mining Methods for Analysis and Forecast of Emerging Technology Trend: A Systematic Mapping Study from SCOPUS Papers.- Machine Learning for Assessment of Cardiometabolic Risk Factors Predictive Potential and Prediction of Obstructive Coronary Arteries Lesions.- Knowledge Engineering.- Application of FCA for Domain Model Theory Investigation.- The Metagraph Model for Complex Networks: Definition, Calculus and Granulation Issues.- Subjective Expert Evaluations in the Model-Theoretic Representation of Object Domain Knowledge.- Multiagent Systems and Robotics.- Q-Mixing Network for Multi-Agent Path Finding in Partially Observable Grid Environments.- Subdefinite Computations for Reducing the Search Space in Mobile Robot Localization Task.- Enhancing Exploration Algorithms for Navigation with Visual SLAM.- Natural Language Processing.- Relying on Discourse Trees to Extract Medical Ontologies from Text.- TITANIS: A Tool for Intelligent Text Analysis in Social Media.- Approach to the Automated Development of Scientific Subject Domain Ontologies Based on Heterogeneous Ontology Design Patterns.- Fuzzy Models and Soft Computing.- PC-algorithm of Algebraic Bayesian Network Secondary Structure Training.- Logistic-based Design of Fuzzy Interpretable Classifiers.- Intelligent Systems.- Knowledge-Based Diagnostic Systemwith a Precedent Library.- Semiotic Models in Monitoring and Decision Support Systems.- Cognitive Patterns for Semantic Presentation of Natural-language Descriptions of Well-formalizable Problems.- Detecting Anomalous Behavior of Users of Data Centers based on the Application of Artificial Neural Networks.- Tools for Designing Intelligent Systems.- Study of the Feasibility of Creating of a Real-time Neuronetwork Infrared Ground Objects Recognition System.- The Implementation of the Ontological Approach to Control of the Processes of Designing Integrated Expert Systems Based on the Problem-oriented Methodology.- A Module for Industrial Safety Inspection Planning Based on Self-organization.-



Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.