Custom cover image
Custom cover image

Intelligent systems and machine learning for industry : advancements, challenges and practices / edited by P.R Anisha, C. Kishor Kumar Reddy, Nguyen Gia Nhu, Megha Bhushan, Marlia Mohd Hanafiah

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Computational methods for industrial applicationsPublisher: Boca Raton : CRC Press, 2022Description: 1 Online-Ressource (1 volume)ISBN:
  • 9781003286745
  • 1003286747
  • 1000828875
  • 9781000828832
  • 1000828832
  • 9781000828870
Subject(s): Additional physical formats: 9781032261447 | 1032261447 | 9781032261447 | Erscheint auch als: Intelligent systems and machine learning for industry. Druck-Ausgabe. Boca Raton : CRC Press, 2022LOC classification:
  • TS183
Online resources: Summary: The book explores the concepts and challenges in developing novel approaches using the Internet of Things, intelligent systems, machine intelligence systems, and data analytics in various industrial sectors such as manufacturing, smart agriculture, smart cities, food processing, environment, defense, stock market and healthcare. Further, it discusses the latest improvements in the industrial sectors using machine intelligence learning and intelligent systems techniques, especially robotics. Features: Highlights case studies and solutions to industrial problems using machine learning and intelligent systems. Covers applications in smart agriculture, smart healthcare, intelligent machines for disaster management, and smart manufacturing. Provides thelatest methodologies using machine intelligence systems in the early forecasting of weather. Examines the research challenges and identifies the gaps in data collection anddata analysis, especially imagery, signal, and speech. Provides applications of digitization and smart processing using the Internet of Things and effective intelligent agent systems in manufacturing. Discusses a systematic and exhaustive analysis of intelligent software effort estimation models. It will serve as an ideal reference text for graduate students, post-graduate students, IT Professionals, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technologyPPN: PPN: 1882643216Package identifier: Produktsigel: ZDB-4-NLEBK | BSZ-4-NLEBK-KAUB
No physical items for this record
KIT – The University in the Helmholtz Association                         Home | Impressum | Datenschutz | Barrierefreiheit | KIT