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Handbook of Research on Data-Driven Mathematical Modeling in Smart Cities

Über Handbook of Research on Data-Driven Mathematical Modeling in Smart Cities

A smart city utilizes ICT technologies to improve the working effectiveness, share various data with the citizens, and enhance political assistance and societal wellbeing. The fundamental needs of a smart and sustainable city are utilizing smart technology for enhancing municipal activities, expanding monetary development, and improving citizens' standards of living. The Handbook of Research on Data-Driven Mathematical Modeling in Smart Cities discusses new mathematical models in smart and sustainable cities using big data, visualization tools in mathematical modeling, machine learning-based mathematical modeling, and more. It further delves into privacy and ethics in data analysis. Covering topics such as deep learning, optimization-based data science, and smart city automation, this premier reference source is an excellent resource for mathematicians, statisticians, computer scientists, civil engineers, government officials, students and educators of higher education, librarians, researchers, and academicians.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9781668464083
  • Einband:
  • Gebundene Ausgabe
  • Seitenzahl:
  • 508
  • Veröffentlicht:
  • 20. Januar 2023
  • Abmessungen:
  • 221x32x286 mm.
  • Gewicht:
  • 1527 g.
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Beschreibung von Handbook of Research on Data-Driven Mathematical Modeling in Smart Cities

A smart city utilizes ICT technologies to improve the working effectiveness, share various data with the citizens, and enhance political assistance and societal wellbeing. The fundamental needs of a smart and sustainable city are utilizing smart technology for enhancing municipal activities, expanding monetary development, and improving citizens' standards of living. The Handbook of Research on Data-Driven Mathematical Modeling in Smart Cities discusses new mathematical models in smart and sustainable cities using big data, visualization tools in mathematical modeling, machine learning-based mathematical modeling, and more. It further delves into privacy and ethics in data analysis. Covering topics such as deep learning, optimization-based data science, and smart city automation, this premier reference source is an excellent resource for mathematicians, statisticians, computer scientists, civil engineers, government officials, students and educators of higher education, librarians, researchers, and academicians.

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