Artificial Intelligence and Industrial Applications

Artificial Intelligence Techniques for Cyber-Physical, Digital Twin Systems and Engineering Applications
Herausgegeben:Masrour, Tawfik; El Hassani, Ibtissam; Cherrafi, Anass

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Lecture Notes in Networks and Systems 144
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-030-53969-6
• 1st ed. 2021
• Seitenzahl: 344
• Erscheinungstermin: 19. Juli 2020
• Englisch
• Abmessung: 235mm x 155mm x 19mm
• Gewicht: 528g
• ISBN-13: 9783030539696
• ISBN-10: 3030539695
• Artikelnr.: 59610065

Inhaltsangabe

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.

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