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
  • [41] PCPartHunter: A Rule-Based Expert System
    Sahari, Muhammad Maziz
    Mabni, Zulaile
    Shamsudin, Noratikah
    [J]. 2019 IEEE 9TH INTERNATIONAL CONFERENCE ON SYSTEM ENGINEERING AND TECHNOLOGY (ICSET), 2019, : 337 - 342
  • [42] Rule-Based Mode Choice Model: INSIM Expert System
    Memon, A. A.
    Meng, M.
    Wong, Y. D.
    Lam, S. H.
    [J]. JOURNAL OF TRANSPORTATION ENGINEERING, 2015, 141 (04)
  • [43] A Type-2 Fuzzy Expert System for Diagnosis of Leukemia
    Asl, Ali Akbar Sadat
    Zarandi, Mohammad Hossein Fazel
    [J]. FUZZY LOGIC IN INTELLIGENT SYSTEM DESIGN: THEORY AND APPLICATIONS, 2018, 648 : 52 - 60
  • [44] Multiobjective Evolutionary Optimization of Type-2 Fuzzy Rule-Based Systems for Financial Data Classification
    Antonelli, Michela
    Bernardo, Dario
    Hagras, Hani
    Marcelloni, Francesco
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2017, 25 (02) : 249 - 264
  • [45] A fuzzy rule-based generation algorithm in interval type-2 fuzzy logic system for fault prediction in the early phase of software development
    Chatterjee, Subhashis
    Maji, Bappa
    Hoang Pham
    [J]. JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE, 2019, 31 (03) : 369 - 391
  • [46] CONNECTIONISM FOR FUZZY LEARNING IN RULE-BASED EXPERT SYSTEMS
    FU, LM
    [J]. LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, 1992, 604 : 337 - 340
  • [47] A FUZZY RULE-BASED EXPERT SYSTEM FOR ASTHMA SEVERITY IDENTIFICATION IN EMERGENCY DEPARTMENT
    Sharif, Nurul Atikah Mohd
    Ahmad, Norazura
    Ahmad, Nazihah
    Desa, Wan Laailatul Hanim Mat
    Helmy, Khaled Mohamed
    Ang, Wei Chern
    Abidin, Ida Zaliza Zainol
    [J]. JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY-MALAYSIA, 2019, 18 (04): : 415 - 438
  • [48] Fuzzy rule-based expert system for short-range seismic prediction
    Klose, CD
    [J]. COMPUTERS & GEOSCIENCES, 2002, 28 (03) : 377 - 386
  • [49] Fuzzy Rule-Based Expert System for Determining Trustworthiness of Cloud Service Providers
    Chahal, Rajanpreet Kaur
    Singh, Sarbjeet
    [J]. INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2017, 19 (02) : 338 - 354
  • [50] Fuzzy Rule-Based Expert System for Determining Trustworthiness of Cloud Service Providers
    Rajanpreet Kaur Chahal
    Sarbjeet Singh
    [J]. International Journal of Fuzzy Systems, 2017, 19 : 338 - 354
12345