國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Data science and multiple criteria d...

Dincer, Hasan.

Data science and multiple criteria decision making approaches in financeapplications and methods /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data science and multiple criteria decision making approaches in financeby Gokhan Silahtaroglu, Hasan Dincer, Serhat Yuksel.
其他題名:	applications and methods /
作者:	Silahtaroglu, Gokhan.
其他作者:	Dincer, Hasan.
出版者:	Cham :Springer International Publishing :2021.
面頁冊數:	xvi, 173 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Multiple criteria decision making.
電子資源:	https://doi.org/10.1007/978-3-030-74176-1
ISBN:	9783030741761$q(electronic bk.)

Data science and multiple criteria decision making approaches in financeapplications and methods /
Silahtaroglu, Gokhan.

Data science and multiple criteria decision making approaches in financeapplications and methods /[electronic resource] :by Gokhan Silahtaroglu, Hasan Dincer, Serhat Yuksel. - Cham :Springer International Publishing :2021. - xvi, 173 p. :ill., digital ;24 cm. - Multiple criteria decision making,2366-0023. - Multiple criteria decision making..

1. Introduction to Data Science and Machine Learning Algorithms -- 2. Identifying Indicators of Global Financial Crisis with Fuzzy Logic and Data Science: A Comparative Analysis between Developing and Developed Economies -- 3. Determining the Ways to Increase Economic Growth of Developing and Developed Economies: An Application with Data Mining and Fuzzy TOPSIS -- 4. Profitability Prediction of Turkish Banking Industry: A Comparative Analysis with Data Science and Fuzzy ANP -- 5. The Influence of the Politicians on Macroeconomic Performance: An Analysis of Donald Trump's Tweets -- 6. How is the Stock Exchange Index Affected by the Disclosures of Politicians? -- 7. Defining the Significant Factors of Currency Exchange Rate Risk by Considering Text Mining and Fuzzy AHP -- 8. Emerging Applications and the Future of Data Science.

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.

ISBN: 9783030741761$q(electronic bk.)

Standard No.: 10.1007/978-3-030-74176-1doiSubjects--Topical Terms:

219475
Multiple criteria decision making.

LC Class. No.: HD30.23 / .S55 2021

Dewey Class. No.: 658.403

Data science and multiple criteria decision making approaches in financeapplications and methods /
LDR:02657nmm a2200349 a 4500 001 598360
003 DE-He213
005 20210529160622.0
006 m d
007 cr nn 008maaau
008 211025s2021 sz s 0 eng d
020 $a 9783030741761$q(electronic bk.)
020 $a 9783030741754$q(paper)
024 7 $a 10.1007/978-3-030-74176-1 $2 doi
035 $a 978-3-030-74176-1
040 $a GP $c GP
041 0 $a eng
050 4 $a HD30.23 $b .S55 2021
072 7 $a KJT $2 bicssc
072 7 $a BUS049000 $2 bisacsh
072 7 $a KJT $2 thema
072 7 $a KJMD $2 thema
082 0 4 $a 658.403 $2 23
090 $a HD30.23 $b .S581 2021
100 1 $a Silahtaroglu, Gokhan. $3 892097
245 1 0 $a Data science and multiple criteria decision making approaches in finance $h [electronic resource] : $b applications and methods / $c by Gokhan Silahtaroglu, Hasan Dincer, Serhat Yuksel.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xvi, 173 p. : $b ill., digital ; $c 24 cm.
490 1 $a Multiple criteria decision making, $x 2366-0023
505 0 $a 1. Introduction to Data Science and Machine Learning Algorithms -- 2. Identifying Indicators of Global Financial Crisis with Fuzzy Logic and Data Science: A Comparative Analysis between Developing and Developed Economies -- 3. Determining the Ways to Increase Economic Growth of Developing and Developed Economies: An Application with Data Mining and Fuzzy TOPSIS -- 4. Profitability Prediction of Turkish Banking Industry: A Comparative Analysis with Data Science and Fuzzy ANP -- 5. The Influence of the Politicians on Macroeconomic Performance: An Analysis of Donald Trump's Tweets -- 6. How is the Stock Exchange Index Affected by the Disclosures of Politicians? -- 7. Defining the Significant Factors of Currency Exchange Rate Risk by Considering Text Mining and Fuzzy AHP -- 8. Emerging Applications and the Future of Data Science.
520 $a 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.
650 0 $a Multiple criteria decision making. $3 219475
650 0 $a Data mining. $3 184440
650 0 $a Fuzzy logic. $3 181981
650 1 4 $a Operations Research/Decision Theory. $3 273963
650 2 4 $a Financial Engineering. $3 744568
650 2 4 $a Operations Research, Management Science. $3 511451
650 2 4 $a Data Structures and Information Theory. $3 825714
650 2 4 $a Artificial Intelligence. $3 212515
700 1 $a Dincer, Hasan. $3 675771
700 1 $a Yuksel, Serhat. $3 815680
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Multiple criteria decision making. $3 731066
856 4 0 $u https://doi.org/10.1007/978-3-030-74176-1
950 $a Business and Management (SpringerNature-41169)