FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4324137798> ?p ?o ?g. }

• W4324137798 endingPage "106106" @default.
• W4324137798 startingPage "106106" @default.
• W4324137798 abstract "Intelligent forecasting model of stock price is an effective way to obtain ideal investment returns. Due to the impact of quantitative transactions, traditional forecasting methods face challenges and pressures. How to find a reliable forecasting model and improve the forecasting accuracy will be a scientific problem worthy of further discussion. This paper proposes an intelligent forecasting model of stock price based on neighborhood rough set (NRS) and multivariate empirical mode decomposition (MEMD) by means of the ideal of “granular computing” and “decomposition ensemble”. Firstly, the multiscale permutation entropy (MPE) method is conducted to determine decision features, which can improve the stability of permutation entropy. Then, a new feature selection method, fusing mutual information (MI) and the NRS, is proposed to automatically capture and select the condition features from the stock market. Subsequently, aiming on revealing the more detailed feature information and maintaining relevance between features, the MEMD is utilized to simultaneously decompose all features. Finally, the decomposed features are inputted into the long short-term memory (LSTM) network to train the intelligent forecasting model and provide the forecasting results of stock price. The validity of our proposed model is assessed through the stocks of Shanghai and Shenzhen markets. The results show that our proposed intelligent forecasting model of stock price makes a beneficial attempt and discussion for the integration of “granular computing” and “decomposition ensemble”. And it will provide scientific support and reference for investors’ actual investment decisions." @default.
• W4324137798 created "2023-03-15" @default.
• W4324137798 creator A5006847732 @default.
• W4324137798 creator A5007803634 @default.
• W4324137798 creator A5041192472 @default.
• W4324137798 creator A5050289757 @default.
• W4324137798 creator A5053701776 @default.
• W4324137798 creator A5060483900 @default.
• W4324137798 date "2023-06-01" @default.
• W4324137798 modified "2023-10-14" @default.
• W4324137798 title "Intelligent forecasting model of stock price using neighborhood rough set and multivariate empirical mode decomposition" @default.
• W4324137798 cites W1782329456 @default.
• W4324137798 cites W1970092360 @default.
• W4324137798 cites W1986078433 @default.
• W4324137798 cites W2118797768 @default.
• W4324137798 cites W2120390927 @default.
• W4324137798 cites W2154053567 @default.
• W4324137798 cites W2158633287 @default.
• W4324137798 cites W2472781479 @default.
• W4324137798 cites W2745759175 @default.
• W4324137798 cites W2886249837 @default.
• W4324137798 cites W2890838230 @default.
• W4324137798 cites W2903508058 @default.
• W4324137798 cites W2947790723 @default.
• W4324137798 cites W2958755640 @default.
• W4324137798 cites W2962940008 @default.
• W4324137798 cites W2981560488 @default.
• W4324137798 cites W2991727127 @default.
• W4324137798 cites W3019427697 @default.
• W4324137798 cites W3049323006 @default.
• W4324137798 cites W3090382853 @default.
• W4324137798 cites W3096794928 @default.
• W4324137798 cites W3110845139 @default.
• W4324137798 cites W3119766002 @default.
• W4324137798 cites W3127303281 @default.
• W4324137798 cites W3159338921 @default.
• W4324137798 cites W3202029859 @default.
• W4324137798 cites W3203211133 @default.
• W4324137798 cites W3211989383 @default.
• W4324137798 cites W3214092996 @default.
• W4324137798 cites W3215479934 @default.
• W4324137798 cites W4205473898 @default.
• W4324137798 cites W4206611675 @default.
• W4324137798 cites W4213276360 @default.
• W4324137798 cites W4214613178 @default.
• W4324137798 cites W4214827063 @default.
• W4324137798 cites W4220686063 @default.
• W4324137798 cites W4224302550 @default.
• W4324137798 cites W4225138819 @default.
• W4324137798 cites W4229446061 @default.
• W4324137798 cites W4280534687 @default.
• W4324137798 cites W4281899822 @default.
• W4324137798 cites W4283460176 @default.
• W4324137798 cites W4285098918 @default.
• W4324137798 cites W4285992182 @default.
• W4324137798 doi "https://doi.org/10.1016/j.engappai.2023.106106" @default.
• W4324137798 hasPublicationYear "2023" @default.
• W4324137798 type Work @default.
• W4324137798 citedByCount "2" @default.
• W4324137798 countsByYear W43241377982023 @default.
• W4324137798 crossrefType "journal-article" @default.
• W4324137798 hasAuthorship W4324137798A5006847732 @default.
• W4324137798 hasAuthorship W4324137798A5007803634 @default.
• W4324137798 hasAuthorship W4324137798A5041192472 @default.
• W4324137798 hasAuthorship W4324137798A5050289757 @default.
• W4324137798 hasAuthorship W4324137798A5053701776 @default.
• W4324137798 hasAuthorship W4324137798A5060483900 @default.
• W4324137798 hasConcept C106301342 @default.
• W4324137798 hasConcept C111012933 @default.
• W4324137798 hasConcept C119857082 @default.
• W4324137798 hasConcept C121332964 @default.
• W4324137798 hasConcept C124101348 @default.
• W4324137798 hasConcept C127413603 @default.
• W4324137798 hasConcept C149782125 @default.
• W4324137798 hasConcept C151730666 @default.
• W4324137798 hasConcept C154945302 @default.
• W4324137798 hasConcept C162324750 @default.
• W4324137798 hasConcept C204036174 @default.
• W4324137798 hasConcept C2780299701 @default.
• W4324137798 hasConcept C2780762169 @default.
• W4324137798 hasConcept C41008148 @default.
• W4324137798 hasConcept C62520636 @default.
• W4324137798 hasConcept C78519656 @default.
• W4324137798 hasConcept C86803240 @default.
• W4324137798 hasConceptScore W4324137798C106301342 @default.
• W4324137798 hasConceptScore W4324137798C111012933 @default.
• W4324137798 hasConceptScore W4324137798C119857082 @default.
• W4324137798 hasConceptScore W4324137798C121332964 @default.
• W4324137798 hasConceptScore W4324137798C124101348 @default.
• W4324137798 hasConceptScore W4324137798C127413603 @default.
• W4324137798 hasConceptScore W4324137798C149782125 @default.
• W4324137798 hasConceptScore W4324137798C151730666 @default.
• W4324137798 hasConceptScore W4324137798C154945302 @default.
• W4324137798 hasConceptScore W4324137798C162324750 @default.
• W4324137798 hasConceptScore W4324137798C204036174 @default.
• W4324137798 hasConceptScore W4324137798C2780299701 @default.
• W4324137798 hasConceptScore W4324137798C2780762169 @default.
• W4324137798 hasConceptScore W4324137798C41008148 @default.

• next