Bandyopadhyay Machine Learning Approaches for Urban Computing

Machine Learning Approaches for Urban Computing

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Beschreibung

This book discusses various machine learning applications and models, developed using heterogeneous data, which helps in a comprehensive prediction, optimization, association analysis, cluster analysis and classification-related applications for various activities in urban area. It details multiple types of data generating from urban activities and suitability of various machine learning algorithms for handling urban data. The book is helpful for researchers, academicians, faculties, scientists and geospatial industry professionals for their research work and sets new ideas in the field of urban computing.

This book discusses various machine learning applications and models, developed using heterogeneous data, which helps in a comprehensive prediction, optimization, association analysis, cluster analysis and classification-related applications for various activities in urban area. It details multiple types of data generating from urban activities and suitability of various machine learning algorithms for handling urban data. The book is helpful for researchers, academicians, faculties, scientists and geospatial industry professionals for their research work and sets new ideas in the field of urban computing.


Discusses various machine learning applications and models Details multiple types of data generating from urban activities Serves as a future guide for researchers and practitioners in academia and industry

Autor*in

Mainak Bandyopadhyay

Themen in »Machine Learning Approaches for Urban Computing«

Urban Computing Machine Learning Urban Data Big Data Social-Media Urban Transportation

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Details

ISBN: 9789811609350
Verlag: Springer Singapore
Erscheinung: 28.04.2021

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