TY  - GEN
AB  - This book considers and assesses essential financial issues by utilizing data science and fuzzy multiple criteria decision making (MCDM) methods. It introduces readers to a range of data science methods, and demonstrates their application in the fields of business, health, economics, finance and engineering. In addition, it provides suggestions based on the assessment results on each topic, which can help to enhance the efficiency of the financial system and the sustainability of economic development. Given its scope, the book will help readers broaden their perspective on the assessment and evaluation of financial issues using data science and MCDM approaches.
AU  - Silahtaroğlu, Gökhan,
AU  - Dinçer, Hasan,
AU  - Yuksel, Serhat,
CN  - HD30.23
DO  - 10.1007/978-3-030-74176-1
DO  - doi
ID  - 1437120
KW  - Data mining.
KW  - Fuzzy logic.
KW  - Multiple criteria decision making.
KW  - Exploration de données (Informatique)
KW  - Logique floue.
KW  - Décision multicritère.
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-74176-1
N1  - Includes index.
N2  - This book considers and assesses essential financial issues by utilizing data science and fuzzy multiple criteria decision making (MCDM) methods. It introduces readers to a range of data science methods, and demonstrates their application in the fields of business, health, economics, finance and engineering. In addition, it provides suggestions based on the assessment results on each topic, which can help to enhance the efficiency of the financial system and the sustainability of economic development. Given its scope, the book will help readers broaden their perspective on the assessment and evaluation of financial issues using data science and MCDM approaches.
SN  - 9783030741761
SN  - 3030741761
T1  - Data science and multiple criteria decision making approaches in finance :applications and methods /
TI  - Data science and multiple criteria decision making approaches in finance :applications and methods /
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-74176-1
ER  -