Advances in Artificial Intelligence: Models, Optimization, and Machine Learning

• Autore: Leon Florin
• Pubblicazione: Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
• Descrizione fisica: 1 online resource (362 p.)
• Soggetto topico: Mathematics and Science; Research and information: general
• Soggetto non controllato: NET framework; adaptive sampling; agent algorithms; agent-based systems; animal-inspired; applied machine learning; approximate differential optimization; autonomous driving; class imbalance; classification; classification and regression; combinatorics; computational complexity; data mining; deep learning; deep neural networks; DeepFKTNet; defect classification; distance metrics; distributed W-learning; dynamic programming algorithm; engineering informatics; ensemble model; evolutionary algorithm; exploitation; exploration; free radical polymerization; gender-based violence in Mexico; generative adversarial networks; graph neural network; hot rolled strip steel; hyperparameters; image classification; inference; instance-based learning; intelligent transport systems; interoperability; k-nearest neighbor; knockout tournament; large margin nearest neighbor regression; machine learning; metaheuristics; multi-agent framework; multi-agent systems; multiple point hill climbing; multisensory fingerprint; n/a; object tracking; optimization; plastic bottle; prototypes; reinforcement learning; simulations; software design; spatial-temporal variable speed limit; stochastic methods; surface defects; traffic control; trajectory prediction; transfer learning; twitter messages; urban motorways
• Persona (resp. second.): HuleaMircea; GavrilescuMarius; LeonFlorin
• Sommario/riassunto: The present book contains all the articles accepted and published in the Special Issue "Advances in Artificial Intelligence: Models, Optimization, and Machine Learning" of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications.
• Altri titoli varianti: Advances in Artificial Intelligence
• Titolo autorizzato: Advances in Artificial Intelligence: Models, Optimization, and Machine Learning
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910580212403321
• Lo trovi qui: Univ. Federico II