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Recent trends in artificial neural networks / Ali Sadollah (2020)  

Public Titre : Recent trends in artificial neural networks Type de document : Monographie Auteurs : Ali Sadollah, Éditeur scientifique ; Carlos M. Travieso-Gonzalez, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2020 Importance : 150 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-1-78985-859-4 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] algorithme génétique [Termes IGN] apprentissage automatique [Termes IGN] apprentissage profond [Termes IGN] classification floue [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection d'objet [Termes IGN] logique floue [Termes IGN] réseau neuronal artificiel Résumé : (éditeur) Artificial intelligence (AI) is everywhere and it's here to stay. Most aspects of our lives are now touched by artificial intelligence in one way or another, from deciding what books or flights to buy online to whether our job applications are successful, whether we receive a bank loan, and even what treatment we receive for cancer. Artificial Neural Networks (ANNs) as a part of AI maintains the capacity to solve problems such as regression and classification with high levels of accuracy. This book aims to discuss the usage of ANNs for optimal solving of time series applications and clustering. Bounding of optimization methods particularly metaheuristics considered as global optimizers with ANNs make a strong and reliable prediction tool for handling real-life application. This book also demonstrates how different fields of studies utilize ANNs proving its wide reach and relevance. Note de contenu : 1- Time series from clustering: An approach to forecast crime patterns 2- Encountered problems of time series with neural networks: Models and architectures 3- Metaheuristics and artificial neural networks 4- An improved algorithm for optimising the production of biochemical systems 5- Object recognition using convolutional neural networks 6- Prediction of wave energy potential in India: A fuzzy-ANN approach 7- Deep learning training and benchmarks for Earth observation images: Data sets, features, and procedures 8- Data mining technology for structural control systems: Concept, development, and comparison Numéro de notice : 28497 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.77409 En ligne : https://doi.org/10.5772/intechopen.77409 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99247