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

Mitwirkende(r):

Anisha, P. R [HerausgeberIn]

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Computational methods for industrial applicationsVerlag: Boca Raton : CRC Press, 2022Beschreibung: 1 Online-Ressource (1 volume)ISBN:

9781003286745
1003286747
1000828875
9781000828832
1000828832
9781000828870

Schlagwörter:

Andere physische Formen: 9781032261447 | 1032261447 | 9781032261447 | Erscheint auch als: Intelligent systems and machine learning for industry. Druck-Ausgabe. Boca Raton : CRC Press, 2022LOC-Klassifikation:

TS183

Online-Ressourcen:

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Zusammenfassung: 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

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