Stock market forecasting using DRAGAN and feature matching

Article Properties
Cite
Shahabi Nejad, Fateme, and Mohammad Mehdi Ebadzadeh. “Stock Market Forecasting Using DRAGAN and Feature Matching”. Expert Systems With Applications, vol. 244, p. 122952, https://doi.org/10.1016/j.eswa.2023.122952.
Shahabi Nejad, F., & Ebadzadeh, M. M. (n.d.). Stock market forecasting using DRAGAN and feature matching. Expert Systems With Applications, 244, 122952. https://doi.org/10.1016/j.eswa.2023.122952
Shahabi Nejad F, Ebadzadeh MM. Stock market forecasting using DRAGAN and feature matching. Expert Systems with Applications. 244:122952.
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Technology
Electrical engineering
Electronics
Nuclear engineering
Electric apparatus and materials
Electric circuits
Electric networks
Technology
Electrical engineering
Electronics
Nuclear engineering
Electronics
Technology
Engineering (General)
Civil engineering (General)
Technology
Manufactures
Production management
Operations management
Technology
Mechanical engineering and machinery
Refrences
Title Journal Journal Categories Citations Publication Date
A novel active multi-source transfer learning algorithm for time series forecasting Applied Intelligence
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Engineering (General). Civil engineering (General)
17 2021
An efficient stock market prediction model using hybrid feature reduction method based on variational autoencoders and recursive feature elimination

Financial Innovation
  • Law: Law in general. Comparative and uniform law. Jurisprudence: Comparative law. International uniform law: Public finance
  • Social Sciences: Finance
  • Social Sciences: Finance
  • Social Sciences: Statistics
  • Social Sciences: Economic theory. Demography: Economics as a science
  • Social Sciences: Commerce: Business
  • Social Sciences: Economic theory. Demography: Economics as a science
28 2021
Stock closing price prediction based on sentiment analysis and LSTM Neural Computing and Applications
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Engineering (General). Civil engineering (General)
123 2020
Stock price forecasting model based on modified convolution neural network and financial time series analysis

International Journal of Communication Systems
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Telecommunication
  • Technology: Engineering (General). Civil engineering (General)
48 2019
A novel hybrid fractal interpolation-SVM model for forecasting stock price indexes Fractals
  • Science: Mathematics
  • Science: Science (General)
  • Science: Mathematics
2019
Refrences Analysis
Category Category Repetition
Science: Mathematics: Instruments and machines: Electronic computers. Computer science11
Technology: Engineering (General). Civil engineering (General)11
Science: Mathematics7
Technology: Manufactures: Production management. Operations management6
Technology: Mechanical engineering and machinery6
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics6
Social Sciences: Economic theory. Demography: Economics as a science5
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks5
Social Sciences: Commerce: Business3
Science: Science (General)3
Social Sciences: Finance2
Technology: Technology (General): Industrial engineering. Management engineering2
Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry2
Science: Physics2
Science: Chemistry2
Science: Science (General): Cybernetics: Information theory2
Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software2
Social Sciences: Statistics1
Science: Biology (General)1
Science: Chemistry: General. Including alchemy1
Technology: Chemical technology1
Technology: Electrical engineering. Electronics. Nuclear engineering: Materials of engineering and construction. Mechanics of materials1
Social Sciences: Commerce: Business: Personnel management. Employment management1
Social Sciences: Industries. Land use. Labor: Management. Industrial management1
Bibliography. Library science. Information resources1
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware1
The category Science: Mathematics: Instruments and machines: Electronic computers. Computer science 11 is the most frequently represented among the references in this article. It primarily includes studies from Expert Systems with Applications The chart below illustrates the number of referenced publications per year.
Refrences used by this article by year