Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods
This paper provides a comprehensive state-of-the-art investigation of the recent advances in data science in emerging economic applications. The analysis is performed on the novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine lea...
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MDPI AG
2020-10-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/8/10/1799 |
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doaj-1d336b0448f243299c28f932542d2c792020-11-25T03:37:35ZengMDPI AGMathematics2227-73902020-10-0181799179910.3390/math8101799Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning MethodsSaeed Nosratabadi0Amirhosein Mosavi1Puhong Duan2Pedram Ghamisi3Ferdinand Filip4Shahab S. Band5Uwe Reuter6Joao Gama7Amir H. Gandomi8Doctoral School of Management and Business Administration, Szent Istvan University, 2100 Godollo, HungaryEnvironmental Quality, Atmospheric Science and Climate Change Research Group, Ton Duc Thang University, Ho Chi Minh, VietnamCollege of Electrical and Information Engineering, Hunan University, Changsha 410082, ChinaHelmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, D-09599 Freiberg, GermanyDepartment of Mathematics, J. Selye University, 94501 Komarno, SlovakiaInstitute of Research and Development, Duy Tan University, Da Nang 550000, VietnamFaculty of Civil Engineering, Technische Universität Dresden, 01069 Dresden, GermanyFaculty Laboratory of Artificial Intelligence and Decision Support (LIAAD)-INESC TEC, Campus da FEUP, Rua Roberto Frias, 4200-465 Porto, PortugalFaculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, AustraliaThis paper provides a comprehensive state-of-the-art investigation of the recent advances in data science in emerging economic applications. The analysis is performed on the novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a broad and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, is used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which outperform other learning algorithms. It is further expected that the trends will converge toward the evolution of sophisticated hybrid deep learning models.https://www.mdpi.com/2227-7390/8/10/1799data sciencedeep learningeconomic modelensembleeconomicscryptocurrency |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Saeed Nosratabadi Amirhosein Mosavi Puhong Duan Pedram Ghamisi Ferdinand Filip Shahab S. Band Uwe Reuter Joao Gama Amir H. Gandomi |
| spellingShingle |
Saeed Nosratabadi Amirhosein Mosavi Puhong Duan Pedram Ghamisi Ferdinand Filip Shahab S. Band Uwe Reuter Joao Gama Amir H. Gandomi Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods Mathematics data science deep learning economic model ensemble economics cryptocurrency |
| author_facet |
Saeed Nosratabadi Amirhosein Mosavi Puhong Duan Pedram Ghamisi Ferdinand Filip Shahab S. Band Uwe Reuter Joao Gama Amir H. Gandomi |
| author_sort |
Saeed Nosratabadi |
| title |
Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods |
| title_short |
Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods |
| title_full |
Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods |
| title_fullStr |
Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods |
| title_full_unstemmed |
Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods |
| title_sort |
data science in economics: comprehensive review of advanced machine learning and deep learning methods |
| publisher |
MDPI AG |
| series |
Mathematics |
| issn |
2227-7390 |
| publishDate |
2020-10-01 |
| description |
This paper provides a comprehensive state-of-the-art investigation of the recent advances in data science in emerging economic applications. The analysis is performed on the novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a broad and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, is used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which outperform other learning algorithms. It is further expected that the trends will converge toward the evolution of sophisticated hybrid deep learning models. |
| topic |
data science deep learning economic model ensemble economics cryptocurrency |
| url |
https://www.mdpi.com/2227-7390/8/10/1799 |
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