Intelligent Technologies and Applications (eBook, PDF)

4th International Conference, INTAP 2021, Grimstad, Norway, October 11-13, 2021, Revised Selected Papers
Redaktion: Sanfilippo, Filippo; Bajwa, Imran Sarwar; Yayilgan, Sule Yildirim; Granmo, Ole-Christoffer

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the 4th International Conference on Intelligent Technologies and Applications, INTAP 2021, held in Grimstad, Norway, October 11-13, 2021.

The 33 full papers included in this book were carefully reviewed and selected from 243 submissions. They were organized in topical sections as follows: Intelligence, Decision support systems, IoT; Robotics; ML and AI for Intelligent Health, Applications of intelligent technologies in Emergency Management; Smart Electrical Energy Systems, AI and ML in Security; ML and AI for sensing technologies, Social Media Analytics; ML in energy sectors and materials; and Miscellaneous.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 434
• Erscheinungstermin: 22. Juli 2022
• Englisch
• ISBN-13: 9783031105258
• Artikelnr.: 64520572

Inhaltsangabe

Intelligence, Decision support systems, IoT.- Dense Nearest Neighborhood Query.- Explainable nonlinear modelling of multiple time series with invertible neural networks.- Iterative Learning for Semi-automatic Annotation Using User Feedback.- Residual Stress Prediction of Welded Joints Using Gradient Boosting Regression.- A Novel Group Teaching Optimization Algorithm based Artificial Neural Network for Classification.- On the Effects of Properties of the Minibatch in Reinforcement Learning.- A novel migration simulation and prediction tool.- Development Environment for Software-defined Smart City Networks.- Robotics.- Branch-Manoeuvring Capable Pipe Cleaning Robot for Aquaponic Systems.- A Multi-Modal Auditory-Visual-Tactile e-Learning Framework.- A Perspective on Intervention Approaches for Children with Autism Spectrum Disorder.- framework for hazard identification of a collaborative Plug&Produce system.- ML and AI for Intelligent Health, Applications of intelligent technologies in Emergency Management.- Future Perspectives on Automated Machine Learning in Biomedical Signal Processing.- DeepFireNet - A Light-Weight Model for Fire-Smoke Classification.- Smart Electrical Energy Systems, AI and ML in Security.- THD Reduction Comparison of Three Phase SPPS via Conventional RC and Novel PRESH Controller.- Artificial Neural Network (ANN) trained by a Novel Arithmetic Optimization Algorithm (AOA) for Short Term Forecasting of Wind Power.- Bode Plot Analysis of PRES and Novel PRESH controller interfaced with three phase GTSPPS.- Energy tracing and blockchain technology: a primary review.- Emulation of IEC 60870-5-104 Communication in Digital Secondary Substations.- ML and AI for sensing technologies, Social Media Analytics.- Point Cloud Instance Segmentation for Automatic Electric Vehicle Battery Disassembly.- Radar-Based Passive Step Counter and its Comparison with a Wrist-Worn Physical Activity Tracker.- Principles for the Arrangement of Social Media Listening Practices in Crisis Management.- AMUSED: An Annotation Framework of Multi-modal Social Media Data.- ML in energy sectors and materials.- An evaluation of predictor variables for photovoltaic power forecasting.- Smart Meter Data Anomaly Detection using Variational Recurrent Autoencoders with Attention.- Detecting the linear and non-linear causal links for disturbances in the power grid.- Machine Learning for PV System Operational Fault Analysis: Literature Review.- Miscellaneous.- An overview of Data Based Predictive Modeling Techniques used in Analysis of Vehicle Crash Severity.- An Evaluation of Autonomous Car Simulators and their applicability for Supervised and Reinforcement Learning.- Classification of Mechanical Fault-Excited Events based on Frequency.- Intelligent Technologies in the Process of Recovering Historical, Cultural, and Heritage Value in Native Communities.- Tensile Experiments on Adhesion between Aluminium Profiles and Glass.- Machine learning for capacity utilization along the routes of an urban freight service.