Intelligent Distributed Computing XII

1. Auflage 2018
ISBN: 978-3-319-99625-7
Verlag: Springer International Publishing

Buch, Englisch, Band 798, 448 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 857 g

Reihe: Studies in Computational Intelligence

This book gathers a wealth of research contributions on recent advances in intelligent and distributed computing, and which present both architectural and algorithmic findings in these fields. A major focus is placed on new techniques and applications for evolutionary computation, swarm intelligence, multi-agent systems, multi-criteria optimization and Deep/Shallow machine learning models, all of which are approached as technological drivers to enable autonomous reasoning and decision-making in complex distributed environments. Part of the book is also devoted to new scheduling and resource allocation methods for distributed computing systems. The book represents the peer-reviewed proceedings of the 12th International Symposium on Intelligent Distributed Computing (IDC 2018), which was held in Bilbao, Spain, from October 15 to 17, 2018.

Zielgruppe

Research

Autoren/Hrsg.

Del Ser, Javier

Osaba, Eneko

Yang, Xin-She

Bilbao, Miren Nekane

Sanchez-Medina, Javier J.

Vecchio, Massimo

Fachgebiete

• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Verteilte Systeme (Netzwerke)
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Part I: Main Track.- Long distance in-links for ranking enhancement.- Concept Tracking and Adaptation for Drifting Data Streams under Extreme Verification Latency.- Adversarial Sample Crafting for Time Series Classification with Elastic Similarity Measures.- Slot Co-allocation Optimization in Distributed Computing with Heterogeneous Resources.- About Designing an Observer Pattern-Based Architecture for a Multi-Objective Metaheuristic Optimization Framework.- Scalable Inference of Gene Regulatory Networks with the Spark Distributed Computing Platform.- Finding Best Compiler Options for Critical Software Using Parallel Algorithms.- Drift Detection over Non-stationary Data Streams using Evolving Spiking Neural Networks.- Part II: Energy.- A Hybrid Ensemble of Heterogeneous Regressors for Wind Speed Estimation in Wind Farms.- Bio-inspired approximation to MPPT under real irradiation conditions.- Part III: Industry.- Decision Making in Industry 4.0 Scenarios supported by Imbalanced Data Classification.