FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313892956> ?p ?o ?g. }

• W4313892956 endingPage "103267" @default.
• W4313892956 startingPage "103267" @default.
• W4313892956 abstract "Constructing ensemble models has become a common method for corporate credit risk early warning, while as to deep learning model with better predictive ability, there have been no fixed theoretical models formed in corporate credit risk early warning, as such models often fail to conduct further qualitative analysis of the results. Thus, this article builds a new two-stage ensemble model using a variety of machine learning methods represented by deep learning for corporate credit risk early warning, which can not only effectively improve the prediction performance of the model, but also qualitatively analyze the source of corporate credit risk from multiple angles according to the results. At first stage, the improved entropy method is used to re-assign the instance weight in correlation degree based on grey correlation analysis. At second stage, this study adopts Bagging method to integrate multiple one-dimensional convolutional neural networks, and borrows idea of N-fold cross validation to expand the difference of the base classifier. Empirically, this article selects listed companies in Chinese manufacturing industry between 2012 and 2021 as datasets, including 467 samples with 51 financial indicators. The new ensemble model has the highest F1-score (87.29%) and G-mean (89.47%) among comparative models, and qualitatively analyzes corporate risk sources. Further, it also analyzes how to increase early warning effect from the angles of indicator number and time span." @default.
• W4313892956 created "2023-01-10" @default.
• W4313892956 creator A5061847709 @default.
• W4313892956 creator A5062980466 @default.
• W4313892956 date "2023-05-01" @default.
• W4313892956 modified "2023-10-13" @default.
• W4313892956 title "A qualitatively analyzable two-stage ensemble model based on machine learning for credit risk early warning: Evidence from Chinese manufacturing companies" @default.
• W4313892956 cites W1966528570 @default.
• W4313892956 cites W1975421067 @default.
• W4313892956 cites W2001753223 @default.
• W4313892956 cites W2015954856 @default.
• W4313892956 cites W2052611008 @default.
• W4313892956 cites W2052796639 @default.
• W4313892956 cites W2060394011 @default.
• W4313892956 cites W2079196938 @default.
• W4313892956 cites W2083862258 @default.
• W4313892956 cites W2147800946 @default.
• W4313892956 cites W2273893358 @default.
• W4313892956 cites W2293081571 @default.
• W4313892956 cites W2565045435 @default.
• W4313892956 cites W2586297576 @default.
• W4313892956 cites W2725536793 @default.
• W4313892956 cites W2761075141 @default.
• W4313892956 cites W2796095619 @default.
• W4313892956 cites W2800569739 @default.
• W4313892956 cites W2804099782 @default.
• W4313892956 cites W2892166671 @default.
• W4313892956 cites W2911450871 @default.
• W4313892956 cites W2956011194 @default.
• W4313892956 cites W2959466452 @default.
• W4313892956 cites W2987213482 @default.
• W4313892956 cites W3000463950 @default.
• W4313892956 cites W3010996902 @default.
• W4313892956 cites W3013460382 @default.
• W4313892956 cites W3026235644 @default.
• W4313892956 cites W3035669514 @default.
• W4313892956 cites W3093033010 @default.
• W4313892956 cites W3093681468 @default.
• W4313892956 cites W3109060525 @default.
• W4313892956 cites W3127303281 @default.
• W4313892956 cites W3154053687 @default.
• W4313892956 cites W3161540856 @default.
• W4313892956 cites W3166239307 @default.
• W4313892956 cites W3173725123 @default.
• W4313892956 cites W3185254425 @default.
• W4313892956 cites W3186703339 @default.
• W4313892956 cites W3197475757 @default.
• W4313892956 cites W3198090055 @default.
• W4313892956 cites W3208873264 @default.
• W4313892956 cites W4205125128 @default.
• W4313892956 cites W4210398911 @default.
• W4313892956 cites W4225357686 @default.
• W4313892956 cites W4281855090 @default.
• W4313892956 cites W993781772 @default.
• W4313892956 doi "https://doi.org/10.1016/j.ipm.2023.103267" @default.
• W4313892956 hasPublicationYear "2023" @default.
• W4313892956 type Work @default.
• W4313892956 citedByCount "2" @default.
• W4313892956 countsByYear W43138929562023 @default.
• W4313892956 crossrefType "journal-article" @default.
• W4313892956 hasAuthorship W4313892956A5061847709 @default.
• W4313892956 hasAuthorship W4313892956A5062980466 @default.
• W4313892956 hasConcept C10138342 @default.
• W4313892956 hasConcept C119857082 @default.
• W4313892956 hasConcept C119898033 @default.
• W4313892956 hasConcept C144133560 @default.
• W4313892956 hasConcept C154945302 @default.
• W4313892956 hasConcept C178350159 @default.
• W4313892956 hasConcept C205208723 @default.
• W4313892956 hasConcept C29825287 @default.
• W4313892956 hasConcept C41008148 @default.
• W4313892956 hasConcept C45942800 @default.
• W4313892956 hasConcept C76155785 @default.
• W4313892956 hasConcept C81363708 @default.
• W4313892956 hasConcept C95623464 @default.
• W4313892956 hasConceptScore W4313892956C10138342 @default.
• W4313892956 hasConceptScore W4313892956C119857082 @default.
• W4313892956 hasConceptScore W4313892956C119898033 @default.
• W4313892956 hasConceptScore W4313892956C144133560 @default.
• W4313892956 hasConceptScore W4313892956C154945302 @default.
• W4313892956 hasConceptScore W4313892956C178350159 @default.
• W4313892956 hasConceptScore W4313892956C205208723 @default.
• W4313892956 hasConceptScore W4313892956C29825287 @default.
• W4313892956 hasConceptScore W4313892956C41008148 @default.
• W4313892956 hasConceptScore W4313892956C45942800 @default.
• W4313892956 hasConceptScore W4313892956C76155785 @default.
• W4313892956 hasConceptScore W4313892956C81363708 @default.
• W4313892956 hasConceptScore W4313892956C95623464 @default.
• W4313892956 hasFunder F4320321001 @default.
• W4313892956 hasFunder F4320321106 @default.
• W4313892956 hasFunder F4320322725 @default.
• W4313892956 hasIssue "3" @default.
• W4313892956 hasLocation W43138929561 @default.
• W4313892956 hasOpenAccess W4313892956 @default.
• W4313892956 hasPrimaryLocation W43138929561 @default.
• W4313892956 hasRelatedWork W1807784185 @default.
• W4313892956 hasRelatedWork W1909207154 @default.
• W4313892956 hasRelatedWork W2139130483 @default.

• next