TY  - GEN
N2  - 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.
DO  - 10.1007/978-981-16-0935-0
DO  - doi
AB  - 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.
T1  - Machine learning approaches for urban computing /
AU  - Bandyopadhyay, Mainak,
AU  - Rout, Minakhi,
AU  - Chandra Satapathy, Suresh.,
VL  - volume 968
CN  - TD159.4
ID  - 1436229
KW  - Smart cities.
KW  - Machine learning.
KW  - Municipal engineering
KW  - Municipal services
KW  - City planning
KW  - Big data.
KW  - Villes intelligentes.
KW  - Apprentissage automatique.
KW  - Génie urbain
KW  - Services municipaux
KW  - Données volumineuses.
SN  - 9789811609350
SN  - 9811609357
TI  - Machine learning approaches for urban computing /
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-0935-0
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-0935-0
ER  -