Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods

• Tipo: Outra Publicação em Revista Científica Internacional
• Data: 2020

Autores

Nosratabadi, S (Autor) Outra; Mosavi, A (Autor) Outra; Duan, P (Autor) Outra; Ghamisi, P (Autor) Outra; Filip, F (Autor) Outra; Band, SS (Autor) Outra; Reuter, U (Autor) Outra; João Gama (Autor) FEP; Gandomi, AH (Autor) Outra

Revista

Título: Mathematics

Vol. 190

Página Final: 1799

Editora: MDPI

Indexação

ISI Web of Knowledge - 82 Citações

Outras Informações

ID Authenticus: P-00T-04Y

DOI: 10.3390/math8101799

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 25