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Machine Learning for Environmental Noise Classification in Smart Cities
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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EUR 56,67
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Proceedings of International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications. ICMISC 2020.
Livre 465 sur 540 : Advances in Intelligent Systems and ComputingVendeur : Universitätsbuchhandlung Herta Hold GmbH, Berlin, Allemagne
Membre d'association : GIAQ ILAB VDA
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Ajouter au panierXVII, 998 p. Softcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Advances in Intelligent Systems and Computing, 1245. Sprache: Englisch.
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Internet of Energy for Smart Cities : Machine Learning Models and Techniques
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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Machine Learning for Environmental Noise Classification in Smart Cities
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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Proceedings of 3rd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications: ICMISC 2022
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Machine Learning for Environmental Noise Classification in Smart Cities (Hardcover)
Langue: anglais
Edité par Springer International Publishing AG, Cham, 2024
ISBN 10 : 3031546660 ISBN 13 : 9783031546662
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
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Ajouter au panierHardcover. Etat : new. Hardcover. We present a Machine Learning (ML) approach to monitoring and classifying noise pollution. Both methods of monitoring and classification have been proven successful. MATLAB and Python code was generated to monitor all types of noise pollution from the collected data, while ML was trained to classify these data. ML algorithms showed promising performance in monitoring the different sound classes such as highways, railways, trains and birds, airports and many more. It is observed that all the data obtained by both methods can be used to control noise pollution levels and for data analytics. They can help decision making and policy making by stakeholders such as municipalities, housing authorities and urban planners in smart cities. The findings indicate that ML can be used effectively in monitoring and measurement. Improvements can be obtained by enhancing the data collection methods. The intention is to develop more ML platforms from which to construct a less noisy. The second objective of this study was to visualize and analyze the data of 18 types of noise pollution that have been collected from 16 different locations in Malaysia. All the collected data were stored in Tableau software. Through the use of both qualitative and quantitative measurements, the data collected for this project was then combined to create a noise map database that can help smart cities make informed decisions. We present a Machine Learning (ML) approach to monitoring and classifying noise pollution. MATLAB and Python code was generated to monitor all types of noise pollution from the collected data, while ML was trained to classify these data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Internet of Energy for Smart Cities : Machine Learning Models and Techniques
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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Machine Learning for Environmental Noise Classification in Smart Cities (Synthesis Lectures on Engineering, Science, and Technology)
Vendeur : Books Puddle, New York, NY, Etats-Unis
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Internet of Energy for Smart Cities : Machine Learning Models and Techniques
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities: Designing for Sustainability (Springer Optimization and Its Applications)
Livre 172 sur 176 : Springer Optimization and Its ApplicationsVendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities: Designing for Sustainability (Springer Optimization and Its Applications, 186)
Livre 172 sur 176 : Springer Optimization and Its ApplicationsVendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Internet of Energy for Smart Cities : Machine Learning Models and Techniques
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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EUR 70
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Internet of Energy for Smart Cities: Machine Learning Models and Techniques
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
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Ajouter au panierPaperback / softback. Etat : New. New copy - Usually dispatched within 4 working days.
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Machine Learning for Environmental Noise Classification in Smart Cities
Vendeur : Revaluation Books, Exeter, Royaume-Uni
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EUR 84,57
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Ajouter au panierHardcover. Etat : Brand New. 187 pages. 9.25x6.10x9.45 inches. In Stock.
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Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities 1ED
Livre 172 sur 176 : Springer Optimization and Its ApplicationsVendeur : Basi6 International, Irving, TX, Etats-Unis
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Ajouter au panierEtat : Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Role Of big Data and Machine Learning In Development of Smart Cities
Langue: anglais
Edité par LAP LAMBERT Academic Publishing, 2021
ISBN 10 : 6203924490 ISBN 13 : 9786203924497
EUR 36,25
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Ajouter au panierTaschenbuch. Etat : Neu. Role Of big Data and Machine Learning In Development of Smart Cities | Hiba Iftikhar | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203924497 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Internet of Energy for Smart Cities: Machine Learning Models and Techniques
Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Ajouter au panierPaperback. Etat : Brand New. 322 pages. 9.18x6.12x9.21 inches. In Stock.
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Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities: Designing for Sustainability (Springer Optimization and Its Applications, 186)
Livre 172 sur 176 : Springer Optimization and Its ApplicationsVendeur : Books Puddle, New York, NY, Etats-Unis
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Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities: Designing for Sustainability (Springer Optimization and Its Applications, 186)
Livre 172 sur 176 : Springer Optimization and Its ApplicationsVendeur : Majestic Books, Hounslow, Royaume-Uni
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Machine Learning for Environmental Noise Classification in Smart Cities
Langue: anglais
Edité par Springer Nature Switzerland, Springer Nature Switzerland, 2025
ISBN 10 : 3031546695 ISBN 13 : 9783031546693
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Ajouter au panierTaschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - We present a Machine Learning (ML) approach to monitoring and classifying noise pollution. Both methods of monitoring and classification have been proven successful. MATLAB and Python code was generated to monitor all types of noise pollution from the collected data, while ML was trained to classify these data. ML algorithms showed promising performance in monitoring the different sound classes such as highways, railways, trains and birds, airports and many more. It is observed that all the data obtained by both methods can be used to control noise pollution levels and for data analytics. They can help decision making and policy making by stakeholders such as municipalities, housing authorities and urban planners in smart cities. The findings indicate that ML can be used effectively in monitoring and measurement. Improvements can be obtained by enhancing the data collection methods. The intention is to develop more ML platforms from which to construct a less noisy. The second objective of this study was to visualize and analyze the data of 18 types of noise pollution that have been collected from 16 different locations in Malaysia. All the collected data were stored in Tableau software. Through the use of both qualitative and quantitative measurements, the data collected for this project was then combined to create a noise map database that can help smart cities make informed decisions.
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Machine Learning for Environmental Noise Classification in Smart Cities
Langue: anglais
Edité par Springer Nature Switzerland, Springer International Publishing, 2024
ISBN 10 : 3031546660 ISBN 13 : 9783031546662
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
EUR 58,84
Expédition à EUR 62,51
Expédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Ajouter au panierBuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - We present a Machine Learning (ML) approach to monitoring and classifying noise pollution. Both methods of monitoring and classification have been proven successful. MATLAB and Python code was generated to monitor all types of noise pollution from the collected data, while ML was trained to classify these data. ML algorithms showed promising performance in monitoring the different sound classes such as highways, railways, trains and birds, airports and many more. It is observed that all the data obtained by both methods can be used to control noise pollution levels and for data analytics. They can help decision making and policy making by stakeholders such as municipalities, housing authorities and urban planners in smart cities. The findings indicate that ML can be used effectively in monitoring and measurement. Improvements can be obtained by enhancing the data collection methods. The intention is to develop more ML platforms from which to construct a less noisy. The second objective of this study was to visualize and analyze the data of 18 types of noise pollution that have been collected from 16 different locations in Malaysia. All the collected data were stored in Tableau software. Through the use of both qualitative and quantitative measurements, the data collected for this project was then combined to create a noise map database that can help smart cities make informed decisions.
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EUR 54,80
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Expédition depuis Allemagne vers Etats-UnisQuantité disponible : 5 disponible(s)
Ajouter au panierTaschenbuch. Etat : Neu. Machine Learning for Environmental Noise Classification in Smart Cities | Ali Othman Albaji | Taschenbuch | Synthesis Lectures on Engineering, Science, and Technology | xvii | Englisch | 2025 | Springer | EAN 9783031546693 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities: Designing for Sustainability (Springer Optimization and Its Applications, 186)
Livre 172 sur 176 : Springer Optimization and Its ApplicationsVendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Évaluation du vendeur 4 sur 5 étoiles
EUR 119,25
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IoT and WSN based Smart Cities: A Machine Learning Perspective (eng)
Livre 117 sur 129 : EAI/Springer Innovations in Communication and ComputingVendeur : Brook Bookstore On Demand, Napoli, NA, Italie
Évaluation du vendeur 4 sur 5 étoiles
EUR 126,26
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Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications : ICMISC 2021
Livre 340 sur 391 : Lecture Notes in Networks and SystemsLangue: anglais
Edité par Springer Nature Singapore, 2022
ISBN 10 : 9811664064 ISBN 13 : 9789811664069
EUR 29,90
Expédition à EUR 105
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Ajouter au panierEtat : Gut. Zustand: Gut | Seiten: 856 | Sprache: Englisch | Produktart: Bücher | This book contains original, peer-reviewed research articles from the Second International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, held in March 28-29th 2021 at CMR Institute of Technology, Hyderabad, Telangana India. It covers the latest research trends and developments in areas of machine learning, artificial intelligence, neural networks, cyber-physical systems, cybernetics, with emphasis on applications in smart cities, Internet of Things, practical data science and cognition. The book focuses on the comprehensive tenets of artificial intelligence, machine learning and deep learning to emphasize its use in modelling, identification, optimization, prediction, forecasting and control of future intelligent systems. Submissions were solicited of unpublished material, and present in-depth fundamental research contributions from a methodological/application perspective in understanding artificial intelligence and machine learning approaches and their capabilities in solving a diverse range of problems in industries and its real-world applications.
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Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities: Designing for Sustainability (Springer Optimization and Its Applications)
Livre 172 sur 176 : Springer Optimization and Its ApplicationsVendeur : Books Puddle, New York, NY, Etats-Unis
Évaluation du vendeur 4 sur 5 étoiles
EUR 137,09
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IoT and WSN based Smart Cities: A Machine Learning Perspective (Hardcover)
Livre 117 sur 129 : EAI/Springer Innovations in Communication and ComputingLangue: anglais
Edité par Springer Nature Switzerland AG, Cham, 2022
ISBN 10 : 3030841812 ISBN 13 : 9783030841812
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
EUR 141,07
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Ajouter au panierHardcover. Etat : new. Hardcover. This book provides an investigative approach to how machine learning is helping to maintain and secure smart cities, including principal uses such as smart monitoring, privacy, reliability, and public protection. The authors cover important areas and issues around implementation roadblocks, ideas, and opportunities in smart city development. The authors also include new algorithms, architectures and platforms that can accelerate the growth of smart city concepts and applications. Moreover, this book provides details on specific applications and case studies related to smart city infrastructures, big data management, and prediction techniques using machine learning. This book provides an investigative approach to how machine learning is helping to maintain and secure smart cities, including principal uses such as smart monitoring, privacy, reliability, and public protection. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities: Designing for Sustainability (Springer Optimization and Its Applications)
Livre 172 sur 176 : Springer Optimization and Its ApplicationsVendeur : Majestic Books, Hounslow, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
EUR 139,60
Expédition à EUR 7,45
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IoT and WSN based Smart Cities A Machine Learning Perspective (eng)
Livre 117 sur 129 : EAI/Springer Innovations in Communication and ComputingVendeur : Brook Bookstore, Milano, MI, Italie
Évaluation du vendeur 4 sur 5 étoiles
EUR 121,53
Expédition à EUR 27,99
Expédition depuis Italie vers Etats-UnisQuantité disponible : 5 disponible(s)
Ajouter au panierEtat : new.
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Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities : Designing for Sustainability
Livre 172 sur 176 : Springer Optimization and Its ApplicationsEUR 51,36
Expédition à EUR 105
Expédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Ajouter au panierEtat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This volume offers a wealth of interdisciplinary approaches to artificial intelligence, machine learning and optimization tools, which contribute to the optimization of urban features towards forming smart, sustainable, and livable future cities.Special features include:New research on the design of city elements and smart systems with respect to new technologies and scientific thinkingDiscussions on the theoretical background that lead to smart cities for the futureNew technologies and principles of research that can promote ideas of artificial intelligence and machine learning in optimized urban environmentsThe book engages students and researchers in the subjects of artificial intelligence, machine learning, and optimization tools in smart sustainable cities as eminent international experts contribute their research results and thinking in its chapters. Overall, its audience can benefit from a variety of disciplines including, architecture, engineering, physics, mathematics, computer science, and related fields.
