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Arai / Bhatia / Kapoor

Intelligent Computing

Proceedings of the 2020 Computing Conference, Volume 2

Medium: Buch
ISBN: 978-3-030-52245-2
Verlag: Springer Nature Switzerland
Erscheinungstermin: 04.07.2020
Lieferfrist: bis zu 10 Tage

This book focuses on the core areas of computing and their applications in the real world. Presenting papers from the Computing Conference 2020 covers a diverse range of research areas, describing various detailed techniques that have been developed and implemented.

The Computing Conference 2020, which provided a venue for academic and industry practitioners to share new ideas and development experiences, attracted a total of 514 submissions from pioneering academic researchers, scientists, industrial engineers and students from around the globe. Following a double-blind, peer-review process, 160 papers (including 15 poster papers) were selected to be included in these proceedings.

Featuring state-of-the-art intelligent methods and techniques for solving real-world problems, the book is a valuable resource and will inspire further research and technological improvements in this important area.


Produkteigenschaften


  • Artikelnummer: 9783030522452
  • Medium: Buch
  • ISBN: 978-3-030-52245-2
  • Verlag: Springer Nature Switzerland
  • Erscheinungstermin: 04.07.2020
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2020
  • Serie: Advances in Intelligent Systems and Computing
  • Produktform: Kartoniert
  • Gewicht: 1089 g
  • Seiten: 717
  • Format (B x H x T): 155 x 235 x 40 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

Urban Mobility Swarms: A Scalable Implementation.- Prediction of Cumulative Grade Point Average: A Case Study.- A Teaching-Learning-based Optimization with Modified Learning Phases for Continuous Optimization.- Use of Artificial Intelligence and Machine Learning for Personalization Improvement in Developed e-Material Formatting Application.- Reduced Order Modeling Assisted By Convolutional Neural Network for Thermal Problems with Nonparametrized Geometrical Variability.- Non-linear Aggregation of Filters to Improve Image Denoising.