Please use this identifier to cite or link to this item:
Title: SAFIN(FRIE)++ : type-I online mandami fuzzy inference system with application in option trading
Authors: Vo Duy Tung
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Issue Date: 2017
Abstract: Fuzzy neural networks are often used to handle dynamic data stream in the financial market. However, unlike stock data that is updated every tick, option data is often sparse in nature. To handle the sparsity in data set, a fuzzy neural network system requires interpolation and extrapolation feature. This paper employs interpolation and extrapolation techniques of [1] to SAFIN++ system in paper of [3] to improve the accuracy of the system when concept drift and shift are detected or when the rule base of the system is sparse. This paper proposes a novel neural fuzzy system architecture called SAFIN++ with Fuzzy Rule Interpolation/Extrapolation that has the following features: a) Online learning feature b) Capable of detect concept shift or drift and handle concept shift or drift using interpolation or extrapolation using multiple multiple-antecedents fuzzy rules c) Rule forgetting or decay memory
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
  Restricted Access
Final Report3.08 MBAdobe PDFView/Open

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.