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    Applied Intelligence for Industry 4.0

    Applied Intelligence for Industry 4.0

    Forfatter: info mangler
    Bog
    • Format
    • Bog, hardback
    • Engelsk

    Beskrivelse

    We are all aware that artificial intelligence (AI) has brought a change in our lives, driven by a new form of interaction between man and machine. We are in the era of the fourth Industrial Revolution (IR) where AI plays vital roles in human development by enabling extraordinary technological advances making fundamental changes to the way we live, work and relate to one another. It is an opportunity to help everyone, including leaders, policymakers and people from all income groups and nations, to harness converging technologies in order to create an inclusive, human-centered future. We need to prepare our graduates as well as researchers to conduct their research with 4.0 IR-related technologies. We need to develop policies and implement those policies to focus on the components of 4.0 IR for sustainable developments. Applied Intelligence for Industry 4.0 will cover cutting edge topics in the fields of AI and industry 4.0. The text will appeal to beginners and advanced researchers in computer science, information sciences, engineering and robotics.

    Features



    Discusses advance data mining, feature extraction and classification algorithms for disease detection, cyber security detection and prevention, soil quality assessment and other industrial applications

    Includes the parameter optimization and explanation of intelligent approaches for business applications

    Presents context-aware smart insights and energy efficient and smart computing for the next-generation of smart industry

    Læs hele beskrivelsen
    Detaljer
    • SprogEngelsk
    • Sidetal260
    • Udgivelsesdato12-06-2023
    • ISBN139781032164151
    • Forlag Chapman & Hall/CRC
    • FormatHardback
    Størrelse og vægt
  • Vægt660 g
    • coffee cup img
    10 cm
    book img
    17,8 cm
    25,4 cm

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    Information retrieval Algorithms Machine learning Human-computer interaction Informatics ai Internet of things Industry 4.0 Gradient boosting Cybersecurity Spam detection Computing Convolutional Neural Network Models Health Informatics Smart computing Feature Selection Techniques Spectrum Sensing Machine learning algorithms Soil quality RF SVM Supervised Machine Learning Vice Versa AdaBoost Classifier Adults Dataset Average Monthly Hours Dataset Split Dengue Case Machine Learning Model MV Technique Naive Bayes Algorithm Machine learning classifiers Hyperparameter Tuning Random Forest Classifier machine learning approach Synthetic Minority Oversampling Technique

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