TY  - GEN
N2  - This book aims to introduce big data solutions in urban sustainability applications—mainly smart transportation and healthcare systems. It focuses on machine learning techniques and data processing approaches which have the capacity to handle/process huge, live, and complex datasets in real-time transportation and healthcare applications. For this, several state-of-the-art data processing approaches including data pre-processing, classification, regression, and clustering are introduced, tested, and evaluated to highlight their benefits and constraints where data is sensitive, real-time, and/or semi-structured.
DO  - 10.1007/978-981-99-6620-2
DO  - doi
AB  - This book aims to introduce big data solutions in urban sustainability applications—mainly smart transportation and healthcare systems. It focuses on machine learning techniques and data processing approaches which have the capacity to handle/process huge, live, and complex datasets in real-time transportation and healthcare applications. For this, several state-of-the-art data processing approaches including data pre-processing, classification, regression, and clustering are introduced, tested, and evaluated to highlight their benefits and constraints where data is sensitive, real-time, and/or semi-structured.
T1  - Big data analytics for smart transport and healthcare systems /
AU  - Ardakani, Saeid Pourroostaei,
AU  - Cheshmehzangi, Ali,
CN  - HE147.6
ID  - 1484652
KW  - Données volumineuses.
KW  - Transport
KW  - Soins médicaux
KW  - Big data.
KW  - Transportation
KW  - Medical care
SN  - 9789819966202
SN  - 9819966205
TI  - Big data analytics for smart transport and healthcare systems /
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-6620-2
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-6620-2
ER  -