Computational Intelligence in Machine Learning - Kumar, Amit; Zurada, Jacek M.; Gunjan, Vinit Kumar;(ed.) - Prospero Internet Bookshop
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Computational Intelligence in Machine Learning: Select Proceedings of ICCIML 2021
 
Product details:
ISBN13:9789811684869
ISBN10:9811684863
Binding:Paperback
No. of pages:528 pages
Size:235x155 mm
Weight:825 g
Language:English
Illustrations: 75 Illustrations, black & white; 219 Illustrations, color
501
Category:

Computational Intelligence in Machine Learning

Select Proceedings of ICCIML 2021
 
Edition number: 1st ed. 2022
Publisher: Springer
Date of Publication:
Number of Volumes: 1 pieces, Book
 
Normal price:
Publisher's listprice:
EUR 481.49
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209 303 HUF (199 336 HUF + 5% VAT)
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Short description:

The book includes select proceedings of the International Conference on Computational Intelligence in Machine Learning (ICCIML 2021). The book constitutes peer-reviewed papers on machine learning, computational intelligence, the internet of things, and smart city applications emphasizing multi-disciplinary research in artificial intelligence and cyber-physical systems. This book addresses the comprehensive nature of computational intelligence, artificial intelligence, machine learning, and deep learning to emphasize its character in modeling, identification, optimization, prediction, forecasting, and control of future intelligent systems. The book will be useful for researchers, research scholars, and students to formulate their research ideas and find future directions in these areas. It will help the readers to solve a diverse range of problems in industries and their real-world applications.

Long description:

The book includes select proceedings of the International Conference on Computational Intelligence in Machine Learning (ICCIML 2021). The book constitutes peer-reviewed papers on machine learning, computational intelligence, the internet of things, and smart city applications emphasizing multi-disciplinary research in artificial intelligence and cyber-physical systems. This book addresses the comprehensive nature of computational intelligence, artificial intelligence, machine learning, and deep learning to emphasize its character in modeling, identification, optimization, prediction, forecasting, and control of future intelligent systems. The book will be useful for researchers, research scholars, and students to formulate their research ideas and find future directions in these areas. It will help the readers to solve a diverse range of problems in industries and their real-world applications.

Table of Contents:
Machine Learning-based Project Resource Allocation Fitment Analysis System ? (ML-PRAFS).- Electric Theft Detection using Un-supervised Machine Learning Based Matrix Profile and K Means Clustering Technique.- Placement Analysis ? A New Approach to Ease the Recruitment Process.- Continuous Assessment Analyzer using Django.- Fuzzy Logic in Battery Energy Storage System (Bess).- Fault Classification of Cooling Fans using a CNN-based Approach.- Violence Recognition using Convolutional Neural Networks.- Automated Grading of Citrus Suhuiensis Fruit using Deep Learning Method.- The Future of Car Automation Field with Smart Driverless Technologies.- Diagnosis and Medicine Prediction for Covid-19 using Machine Learning Approach.- Automated Guided Vehicle Robot Localization with Sensor Fusion.- Implementation of Industrial Automation Water Distribution System Utilizing PLC: A Laboratory Set-up.- Control of Thin McKibben Muscles in an Antagonistic Pair Configuration.- Defect Severity Classification of Complex Composites using CWT and CNN.- Detection of Mobile Phone Usage While Driving using Computer Vision and Deep Learning.- Industry Revolution 4.0 Knowledge Assessment in Malaysia.