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  • Produktbild: Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering
  • Produktbild: Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering

Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering

Aus der Reihe Intelligent Data-Centric Systems

116,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

22.03.2022

Abbildungen

110 illustrations (20 in full color)

Herausgeber

Goncalo Marques + weitere

Verlag

Elsevier Science & Technology

Seitenzahl

474

Maße (L/B/H)

23,5/19,1/2,4 cm

Gewicht

809 g

Sprache

Englisch

ISBN

978-0-323-85597-6

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

22.03.2022

Abbildungen

110 illustrations (20 in full color)

Herausgeber

Verlag

Elsevier Science & Technology

Seitenzahl

474

Maße (L/B/H)

23,5/19,1/2,4 cm

Gewicht

809 g

Sprache

Englisch

ISBN

978-0-323-85597-6

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering
  • Produktbild: Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering

  • Section I: Data-centric and intelligent systems in air quality monitoring, assessment and mitigation
    1. Application of deep learning and machine learning in air quality modelling
    2. Case study of air quality prediction by deep learning and machine learning
    3. Considerations of particle dispersion modelling with data-centric and intelligent systems
    4. Data-centric modelling of air filters, HVAC and other industrial air quality control systems
    5. A review of recent developments and applications of data-centric systems in air quality monitoring, assessment and mitigation

    Section 2: Data-centric and intelligent systems in water quality monitoring, assessment and mitigation
    6. Application of deep learning and machine learning methods in water quality modelling and prediction
    7. Case studies of surface water, groundwater and rainwater quality prediction by data-centric and intelligent systems
    8. Application of deep learning and machine learning methods in contaminant hydrology
    9. Deep learning and machine learning methods in emerging contaminants and micro-pollutants research
    10. A review of recent developments and applications of data-centric systems in water quality monitoring, assessment and mitigation

    Section 3: Data-centric and intelligent systems inland pollution research
    11. Application of deep learning and machine learning methods in flow modelling of landfill leachate
    12. Case studies of evaluations and analysis of solid waste management techniques by deep learning and machine learning methods
    13. Application of deep learning and machine learning methods in soil quality assessment and remediation
    14. Establishing a nexus between non-biodegradable waste and data-centric systems
    15. A review of recent developments and applications of data-centric systems inland pollution research

    Section 4: Data-centric and intelligent systems in noise pollution research
    16. Methods development for data-centric systems in noise pollution research
    17. Case studies of data-centric systems in noise pollution research
    18. A review of recent developments and applications of data-centric systems in noise pollution research