Machine Learning for Networking: Lecture Notes in Computer Science, cartea 11407
Editat de Éric Renault, Paul Mühlethaler, Selma Boumerdassien Limba Engleză Paperback – 10 mai 2019
The 22 revised full papers included in the volume were carefully reviewed and selected from 48 submissions. They present new trends in the following topics: Deep and reinforcement learning; Pattern recognition and classification for networks; Machine learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection; Optimization and new innovative machine learning methods; Performance analysis of machine learning algorithms; Experimental evaluations of machine learning; Data mining in heterogeneous networks; Distributed and decentralized machine learning algorithms; Intelligent cloud-support communications, resource allocation, energy-aware/green communications, software defined networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.
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Specificații
ISBN-13: 9783030199449
ISBN-10: 3030199444
Pagini: 404
Ilustrații: XIII, 388 p. 208 illus., 156 illus. in color.
Dimensiuni: 155 x 235 x 22 mm
Greutate: 0.61 kg
Ediția:1st ed. 2019
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
ISBN-10: 3030199444
Pagini: 404
Ilustrații: XIII, 388 p. 208 illus., 156 illus. in color.
Dimensiuni: 155 x 235 x 22 mm
Greutate: 0.61 kg
Ediția:1st ed. 2019
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
Cuprins
Learning Concave-Convex Profiles of Data Transport Over Dedicated Connections.- Towards Analyzing C-ITS Security Data.- Towards a Statistical Approach for User Classification in Twitter.- RILNET: A Reinforcement Learning Based Load Balancing Approach for Datacenter Networks.- Building a Wide-Area File Transfer Performance Predictor: An Empirical Study.- Advanced Hybrid Technique in Detecting Cloud Web Application's Attacks.- Machine-Learned Classifiers for Protocol Selection on a Shared Network.- Common Structures in Resource Management as Driver for Reinforcement Learning: a Survey and Research Tracks.- Inverse Kinematics Using Arduino and Unity for People with Motor Skill Limitations.- Delmu: A Deep Learning Approach to Maximizing the Utility of Virtualised Millimetre-Wave Backhauls.- Malware Detection System Based on an In-depth Analysis of the Portable Executable Headers.- DNS Traffic Forecasting Using Deep Neural Networks.- Energy-Based Connected Dominating Set for Data Aggregation for Intelligent Wireless Sensor Networks.- Touchless Recognition of Hand Gesture Digits and English Characters Using Convolutional Neural Networks.- LSTM Recurrent Neural Network for Anomaly Detection in Cellular Mobile Networks.- Towards a Better Compromise Between Shallow and Deep CNN for Binary Classification Problems of Unstructured Data.- Reinforcement Learning Based Routing Protocols Analysis for Mobile Ad-Hoc Networks.- Deep Neural Ranking for Crowdsourced Geopolitical Event Forecasting.- The Comment of BBS: How Investor Sentiment Affects a Share Market of China.- A Hybrid Neural Network Approach for Lung Cancer Classification with Gene Expression Dataset and Prior Biological Knowledge.- Plant Leaf Disease Detection and Classification Using Particle Swarm Optimization.- A Game Theory Approach for Intrusion Prevention Systems.- WSN Heterogeneous Architecture Platform for IoT.- An IoT Framework for Detecting Movement Within Indoor Environments.- A Hybrid Architecture for Cooperative UAV and USV Swarm Vehicles.- Detecting Suspicious Transactions in Smart Living Spaces.- Intelligent ERP Based Multi Agent Systems and Cloud Computing.