Artificial Intelligence and Industrial Applications

This book gathers the refereed proceedings of the Artificial Intelligence and Industrial Applications (A2IA'2020), the first installment of an annual international conference organized by the ENSAM-Meknes at Moulay Ismail University, Morocco.

The 30 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 smart manufacturing, smart maintenance, smart supply chain management, supervised learning, unsupervised learning, reinforcement learning, graph-based and semi-supervised learning, neural networks, deep learning, planning and optimization, and other AI applications.

The book is intended for AI experts, offering them a valuable overview of the status quo and a global outlook for the future, with many new and innovative ideas and recent important developments 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.

Autorentext
Dr. Tawfik Masrour is a Professor of Applied Mathematics and Artificial Intelligence at ENSAM-Meknes, Moulay Ismail University UMI, and member of the Artificial Intelligence for Engineering Sciences (AIES) Research Team and Laboratory of Mathematical Modeling, Simulation and Smart Systems (L2M3S). He graduated from Mohammed V University Rabat with an M.Sc. degree in Applied Mathematics and Numerical Analysis, and from Jacques-Louis Lions Laboratory, Pierre and Marie Curie University, Paris, with an M.A.S. (DEA) in Applied Mathematics, Numerical Analysis and Computer Science. He obtained his Ph.D. in Mathematics and Informatics from the École des Ponts ParisTech (ENPC), Paris, France. His research interests include control theory and artificial intelligence.
Dr. Anass Cherrafi is an Assistant Professor at the Department of Industrial Engineering, ENSAM-Meknes, Moulay Ismail University UMI, Morocco. Holding a Ph.D. in Industrial Engineering, he has seven years of industry and teaching experience. He has published a number of articles in leading international journals and conference proceedings, and has been a Guest Editor for special issues of various international journals. His research interests include Industry 4.0, green manufacturing, Lean Six Sigma, integrated management systems and supply chain management.
Dr. Ibtissam El Hassani is a Professor of Industrial and Logistic Engineering at ENSAM-Meknes, Moulay Ismail University UMI, Morocco and Head of the Artificial Intelligence for Engineering Sciences (AIES) Research Team. She graduated as an Industrial Engineer before completing her Ph.D. in Computer Engineering & Systems Supervision at the Center for Doctoral Studies, Moulay Ismail University. Her research interests include applications of artificial intelligence in industrial engineering, especially in lean manufacturing, Six Sigma and continuous improvement, production systems, quality management systems, health and security at work, supply chain management and industrial risk management.

Inhalt

A Fuzzy Ontology Based Approach To Support Product Eco-Design.- .- A Genetic-based SVM Approach for Quality Data Classification.- Towards a platform to implement an intelligent and predictive maintenance in the context of industry.- Towards a Prediction Analysis in an Industrial Context.- Methodology for Implementation of Industry . Technologies in Supply Chain for SMEs.- A Deep Reinforcement Learning DRL Decision Model For Heating Process Parameters Identification In Automotive Glass Manufacturing .- Analytic Hierarchy Process AHP for supply chain . risks management.- SmartDFRelevance: a Holonic Agent based System for Engineering Industrial Projects in Concurrent Engineering Context.- A Cyber-Physical Warehouse Management System Architecture in an.- Industry . context.- PLM and Smart technologies for product and supply chain design.- Production systems simulation considering Non-Productive Times and Human Factors.- Distributed and Embedded System to Control Traffic Collision Based on Artificial Intelligence.- The Emergence and Decision Support in Complex System with Fuzzy Logic Control.- Markov Decision Processes with Discounted Costs over a Finite Horizon: Action Elimination.- Robust adaptive fuzzy path tracking control of Differential Wheeled Mobile Robot.- Deep Learning approach for Automated Guided Vehicle System.- Path Planning Using Particle Swarm Optimization And Fuzzy Logic .- Prediction of Robot localization states using Hidden Markov Models.- A New Approach for Multi-Agent Reinforcement Learning.- Recommender System for Most Relevant k Pick-Up Points.- Feature Detection and Tracking for Visual Effects: Augmented Reality and Video Stabilization.- Spectral image recognition using artificial dynamic neural network in information resonance mode.- U-Net Based Model for Obfuscated Human Faces Reconstruction.- A Machine Learning Assistant for Choosing Operators and Tuning Their Parameters in Image Processing Tasks.- Convergence and parameters setting of continuous Hopfield neural networks applied to image restoration problem.- The Ibn Battouta Air Traffic Control Corpus with Real Life ADS-B and METAR data.- Weed Recognition System For Low-Land Rice Precision Farming Using Deep Learning Approach.- A Comparative Study Between Mixture and Stepwise Regression to Model The Parameters Of The Composting Process.- Deep Learning Based Sponge Gourd Diseases Recognition For Commercial Cultivation in Bangladesh.- Exploitation of vegetation indices and Random Forest for cartography of rosemary cover: application to Gourrama region, Morocco.