Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorPanuwit Pholkerden_US
dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.contributor.authorNipon Theera-Umponen_US
dc.description.abstract© 2020, Springer Nature Switzerland AG. Companies with the Trading Suspension (SP), and Non-Compliance (NC) sign posted might run a risk of bankruptcy. One would want to predict the SP or NC sign posted before it is posted to help in investing decision. In this paper, we introduce the prediction system using fuzzy hybrid operator with swarm intelligence optimization algorithm. In particular, we utilize the gamma operator with firefly, grey wolf, and social spider algorithms. The gamma operator with social spider yields 92.45% correct prediction result. We also compare our result with the support vector machine (SVM). The SVM yields 100% correct prediction. Although, the gamma operator is worse than SVM, the gamma operator can provide an influence information of inputs to the prediction output. The gamma operator provides that the debt ratio from the 8th previous quarter is the most influential input to the prediction whereas that from the 2nd to 6th previous quarters have small effect to the prediction.en_US
dc.subjectComputer Scienceen_US
dc.titleCompanies Trading Signs Prediction Using Fuzzy Hybrid Operator with Swarm Optimization Algorithmsen_US
dc.typeBook Seriesen_US
article.title.sourcetitleAdvances in Intelligent Systems and Computingen_US
article.volume1072en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.

Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.