Buch, Englisch, 324 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 522 g
Artificial Intelligence Techniques for Cyber-Physical, Digital Twin Systems and Engineering Applications
Buch, Englisch, 324 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 522 g
Reihe: Lecture Notes in Networks and Systems
ISBN: 978-3-030-53969-6
Verlag: Springer International Publishing
This book gathers selected papers from Artificial Intelligence and Industrial Applications (A2IA’2020), the first installment of an annual international conference organized by ENSAM-Meknes at Moulay Ismail University, Morocco.
The 29 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as digital twin, multiagent systems, deep learning, image processing and analysis, control, prediction, modeling, optimization and design, as well as AI applications in industry, health, energy, agriculture, and education.
The book is intended for AI experts, offering them a valuable overview and global outlook for the future, and highlights a wealth of innovative ideas and recent, important advances in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Technische Wissenschaften Verkehrstechnik | Transportgewerbe Intelligente & automatisierte Transportsysteme
- Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
- Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
Weitere Infos & Material
A Study of Energy Reduction Strategies in Renewable Hybrid Grid.- Classification and Watermarking of Brain Tumor using Artificial and Convolutional Neural Networks.- A Proposal for a Deep Learning Model to Enhance Student Guidance and Reduce Dropout.- EduBot: An Unsupervised Domain-Specific Chatbot for Educational Institutions.- SQL Generation from Natural Language using Supervised Learning and Recurrent Neural Networks.- Toward Intelligent Solution to Identify Learner Attitude from Source Code.
