An interpretable Neural Fuzzy Hammerstein-Wiener network for stock price prediction

An interpretable regression model is proposed in this paper for stock price prediction. Conventional offline neuro-fuzzy systems are only able to generate implications based on fuzzy rules induced during training, which requires the training data to be able to adequately represent all system behavio...

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Bibliographic Details
Main Authors: Xie, Chen, Rajan, Deepu, Chai, Quek
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2022
Subjects:
Online Access:https://hdl.handle.net/10356/159511
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Institution: Nanyang Technological University
Language: English