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[null,"1.","Record Nr.",null,"UNINA9910710289703321"]
[null,null,"Autore",null,"Lee B. T"]
[null,null,"Titolo",null,"Fire performance guidelines for shipboard interior finish / / B. T. Lee; W. J. Parker"]
[null,null,"Pubbl/distr/stampa",null,"Gaithersburg, MD : , : U.S. Dept. of Commerce, National Institute of Standards and Technology, , 1979"]
[null,null,"Descrizione fisica",null,"1 online resource"]
[null,null,"Collana",null,"NBSIR ; ; 79-1700"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","1979."]
[{"$nulls":4},"Contributed record: Metadata reviewed, not verified. Some fields updated by batch processes."]
[{"$nulls":4},"Title from PDF title page."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,"2.","Record Nr.",null,"UNINA9910838282603321"]
[null,null,"Autore",null,"Gunjan Vinit Kumar"]
[null,null,"Titolo",null,"Computational Intelligence in Machine Learning : Proceedings of the 2nd International Conference ICCIML 2022 / / edited by Vinit Kumar Gunjan, Amit Kumar, Jacek M. Zurada, Sri Niwas Singh"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"9789819979547"]
[{"$nulls":4},"9819979544"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (686 pages)"]
[null,null,"Collana",null,"Lecture Notes in Electrical Engineering, , 1876-1119 ; ; 1106"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Machine learning"]
[{"$nulls":4},"Artificial intelligence - Data processing"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Machine Learning"]
[{"$nulls":4},"Data Science"]
[{"$nulls":4},"Artificial Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"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 "]
[{"$nulls":4},"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."]
[null,null,null,"Sommario/riassunto","This 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."]