An interpretable neural fuzzy inference system for predictions of underpricing in initial public offerings
Due to their aptitude in both accurate data processing and human comprehensible reasoning, neural fuzzy inference systems have been widely adopted in various application domains as decision support systems. Especially in real-world scenarios such as decision making in financial transactions, the hum...
Main Authors: | Qian, Xiaolin, Quek, Chai, Miao, Chunyan, Wang, Di, Zhang, Xiaofeng, Ng, Geok See, Zhou, You, Tan, Ah-Hwee |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2018
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/80561 http://hdl.handle.net/10220/46696 |
Similar Items
-
Leveraging the trade-off between accuracy and interpretability in a hybrid intelligent system
by: Miao, Chunyan, et al.
Published: (2018) -
A framework of modified adaptive neuro-fuzzy inference engine
by: Hossen, Md. Jakir
Published: (2012) -
RIT2FIS : a recurrent interval type 2 Fuzzy Inference System and its rule base estimation
by: Samanta, Subhrajit, et al.
Published: (2019) -
Smart interpretable model (SIM) enabling subject matter experts in rule generation
by: Christianto, Hotman, et al.
Published: (2022) -
Interpretable fault diagnosis with shapelet temporal logic: theory and application
by: Chen, Gang, et al.
Published: (2022)