A type-2 fuzzy rule-based expert system model for stock price analysis

被引：128
|
作者：
Zarandi, M. H. Fazel [1 ]
Rezaee, B. [1 ]
Turksen, I. B. [2 ]
Neshat, E. [1 ]
机构：
[1] Amirkabir Univ Technol, Polytech Tehran, Dept Ind Engn, Tehran, Iran
[2] Univ Toronto, Dept Mech & Ind Engn, Toronto, ON M5S2 H8, Canada
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2009年 / 36卷 / 01期
关键词：
Type-2 fuzzy modeling; Fuzzy rule based systems; Forecasting; Stock market; CLUSTER-VALIDITY; LOGIC SYSTEMS; INDEX; SETS;
D O I：
10.1016/j.eswa.2007.09.034
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a type-2 fuzzy rule based expert system is developed for stock price analysis. Interval type-2 fuzzy logic system permits us to model rule uncertainties and every membership value of an element is interval itself. The proposed type-2 fuzzy model applies the technical and fundamental indexes as the input variables. This model is tested on stock price prediction of an automotive manufactory in Asia. Through the intensive experimental tests, the model has successfully forecasted the price variation for stocks from different sectors. The results are very encouraging and can be implemented in a real-time trading system for stock price prediction during the trading period. (C) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码：139 / 154
页数：16
相关论文
共 50 条
  • [1] A Type-2 Fuzzy Rule-Based Expert System Model for Portfolio Selection
    Zarandi, M. H. Fazel
    Yazdi, E. Hajigol
    [J]. PROCEEDINGS OF THE 11TH JOINT CONFERENCE ON INFORMATION SCIENCES, 2008,
  • [2] Type-2 Fuzzy Rule-based Expert System for Ankylosing spondylitis Diagnosis
    Maftouni, Maede
    Zarandi, M. H. Fazel
    Turksen, I. B.
    Roshani, Faezeh
    [J]. 2015 Annual Meeting of the North American Fuzzy Information Processing Society DigiPen NAFIPS 2015, 2015,
  • [3] Fuzzy Clustering Rule-Based Expert System for Stock Price Movement Prediction
    Shakeri, Behnoush
    Zarandi, M. H. Fazel
    Tarimoradi, Mosahar
    Turksan, I. B.
    [J]. 2015 Annual Meeting of the North American Fuzzy Information Processing Society DigiPen NAFIPS 2015, 2015,
  • [4] Type-2 fuzzy rule-based expert system for diagnosis of spinal cord disorders
    Damirchi-Darasi, S. Rahimi
    Zarandi, M. H. Fazel
    Turksen, I. B.
    Izadi, M.
    [J]. SCIENTIA IRANICA, 2019, 26 (01) : 455 - 471
  • [5] Type-2 interval fuzzy rule-based systems in spatial analysis
    Di Martino, Ferdinando
    Sessa, Salvatore
    [J]. INFORMATION SCIENCES, 2014, 279 : 199 - 212
  • [6] A Fuzzy Rule-Based Classification System Using Interval Type-2 Fuzzy Sets
    Tang, Min
    Chen, Xia
    Hu, Weidong
    Yu, Wenxian
    [J]. INTEGRATED UNCERTAINTY IN KNOWLEDGE MODELLING AND DECISION MAKING, 2011, 7027 : 72 - +
  • [7] A type-2 fuzzy rule-based model for diagnosis of COVID-19
    Sahin, Ihsan
    Akdogan, Erhan
    Aktan, Mehmet Emin
    [J]. TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2023, 31 (01) : 39 - 52
  • [8] ON LEARNING IN A FUZZY RULE-BASED EXPERT SYSTEM
    GEYERSCHULZ, A
    [J]. KYBERNETIKA, 1992, 28 : 33 - 36
  • [9] A Fuzzy Rule-based Classification System using Hedge Algebraic Type-2 Fuzzy Sets
    Phan Anh Phong
    Tran Dinh Khang
    Dinh Khac Dong
    [J]. 2016 ANNUAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY (NAFIPS), 2016,
  • [10] Fuzzy Rule-Based Stock Trading System
    Yeh, I-Cheng
    Lien, Che-hui
    [J]. IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ 2011), 2011, : 2066 - 2072
12345