Description

Book Synopsis

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.

Computational Intelligence in Machine Learning:

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£332.49

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Order before 4pm today for delivery by Fri 23 Jan 2026.

A Hardback by Amit Kumar, Jacek M. Zurada, Vinit Kumar Gunjan

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    View other formats and editions of Computational Intelligence in Machine Learning: by Amit Kumar

    Publisher: Springer Verlag, Singapore
    Publication Date: 04/03/2022
    ISBN13: 9789811684838, 978-9811684838
    ISBN10: 9811684839

    Description

    Book Synopsis

    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.

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