04463nam a22005535i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050000900172072001600181072002300197072001500220245021600235250001800451264007200469300006700541336002600608337002600634338003600660347002400696490006400720505121300784520097501997650003902972650002903011650004603040650003603086650003903122650002903161650001803190650003603208700008903244700008103333700008503414700008603499710003403585773002603619776003603645776003603681776003603717830006403753856004603817912001403863912001503877999001703892978-981-99-7954-7DE-He21320251030111435.0cr nn 008mamaa240220s2024    si |    s    |||| 0|eng d  a97898199795479978-981-99-7954-77 a10.1007/978-981-99-7954-72doi 4aQ342 7aUYQ2bicssc 7aCOM0040002bisacsh 7aUYQ2thema10aComputational Intelligence in Machine Learningh[electronic resource] :bProceedings of the 2nd International Conference ICCIML 2022 /cedited by Vinit Kumar Gunjan, Amit Kumar, Jacek M. Zurada, Sri Niwas Singh.  a1st ed. 2024. 1aSingapore :bSpringer Nature Singapore :bImprint: Springer,c2024.  aXII, 707 p. 385 illus., 318 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aLecture Notes in Electrical Engineering,x1876-1119 ;v11060 aMachine 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.  aThis volumes comprises select proceedings of the International Conference on Computational Intelligence in Machine Learning (ICCIML 2022). The contents cover latest research trends and developments in the areas of machine learning, smart cities, IoT, Artificial Intelligence, cyber physical systems, cybernetics, data science, neural network, cognition, among others. It also addresses the comprehensive nature of computational intelligence, AI, ML and DL to emphasize its character in modelling, identification, optimization, prediction, forecasting, and control of future intelligent systems. This volume will be a useful guide to those working as researchers in academia and industry by presenting in-depth fundamental research contributions from a methodological/application perspective in understanding Artificial intelligence and machine learning approaches and their capabilities in solving diverse range of problems in industries and its real-world applications. 0aComputational intelligence.964052 0aMachine learning.955059 0aArtificial intelligencexData processing. 0aArtificial intelligence.95844114aComputational Intelligence.96405224aMachine Learning.95505924aData Science.24aArtificial Intelligence.9584411 aGunjan, Vinit Kumar.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9680151 aKumar, Amit.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9659641 aZurada, Jacek M.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9695301 aSingh, Sri Niwas.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9698562 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978981997953008iPrinted edition:z978981997955408iPrinted edition:z9789819979561 0aLecture Notes in Electrical Engineering,x1876-1119 ;v110640uhttps://doi.org/10.1007/978-981-99-7954-7  aZDB-2-INR  aZDB-2-SXIT  c57763d57763