Evaluating industry performance using extracted RGR rules based on feature selection and rough sets classifier-Reference-Cited by-同舟云学术

Evaluating industry performance using extracted RGR rules based on feature selection and rough sets classifier

Published:2009-07 Issue:5 Volume:36 Page:9448-9456
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Chen You-Shyang,Cheng Ching-Hsue

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference46 articles.

1. Fundamental analysis, future earnings, and stock prices;Abarbanell;Journal of Accounting Research,1997

2. Evaluating students’ learning achievement using fuzzy membership functions and fuzzy rules;Bai;Expert Systems with Applications,2008

3. Rough set algorithms in classification problem;Bazan,2000

4. RSES and RSESlib – A collection of tools for rough set, lecture notes in computer science, 2005;Bazan,2001

5. Bedworth, M. D., Lowe, D. (1988). Fault tolerance in multi-layer perceptrons: A preliminary study. RSRE: Pattern Processing and Machine Intelligence Division.

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Feature Selection Algorithm Based on CFS Algorithm Emphasizing Data Discrimination;2023-09-08

2. A new hybrid financial time series prediction model;Engineering Applications of Artificial Intelligence;2020-10

3. A modular Takagi-Sugeno-Kang (TSK) system based on a modified hybrid soft clustering for stock selection;Scientia Iranica;2019-10-20

4. Logical rules characterization of online consumer trust;International Transactions in Operational Research;2019-01-24

5. iTrade;Intelligent Systems;2018