Type-2 interval fuzzy rule-based systems in spatial analysis

被引：10
|
作者：
Di Martino, Ferdinando [1 ]
Sessa, Salvatore [1 ,2 ]
机构：
[1] Univ Naples Federico II, Dipartimento Architettura, I-80134 Naples, Italy
[2] Univ Naples Federico II, Ctr Interdipartimentale Ric Anal & Progettaz Urba, I-80134 Naples, Italy
来源：
INFORMATION SCIENCES | 2014年 / 279卷
关键词：
Interval type-2 fuzzy set; IT2-FS rule-based system; GIS; Spatial analysis; LOGIC SYSTEMS; VULNERABILITY; GIS;
D O I：
10.1016/j.ins.2014.03.114
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper we present a rule-based system by using interval type-2 fuzzy sets (IT2-FS) for solving problems of spatial analysis. This system is encapsulated in a Geographical Information System (GIS) by performing numerous tests for evaluating their reliability. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码：199 / 212
页数：14
相关论文
共 50 条
  • [1] Fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on interval type-2 fuzzy sets
    Chen, Shyi-Ming
    Lee, Li-Wei
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (08) : 9947 - 9957
  • [2] Generating Interval Type-2 Fuzzy Inputs from Smoothed Data for Fuzzy Rule-Based Systems
    Sussner, Peter
    Alencar, Tiago da Silva
    [J]. APPLICATIONS OF FUZZY TECHNIQUES, NAFIPS 2022, 2023, 500 : 255 - 266
  • [3] 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 - +
  • [4] Fuzzy Rules Interpolation for Sparse Fuzzy Rule-Based Systems Based on Interval Type-2 Gaussian Fuzzy Sets and Genetic Algorithms
    Chen, Shyi-Ming
    Chang, Yu-Chuan
    Pan, Jeng-Shyang
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2013, 21 (03) : 412 - 425
  • [5] Learning Type-2 Fuzzy Rule-Based Systems through Memetic Algorithms
    Acampora, Giovanni
    D'Alterio, Pasquale
    Vitiello, Autilia
    [J]. 2018 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2018,
  • [6] An new interval type-2 hybrid fuzzy rule-based AHP system for supplier selection
    Ozturk, Muslum
    Paksoy, Turan
    [J]. JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY, 2020, 35 (03): : 1519 - 1535
  • [7] Comparing the Performance Potentials of Interval and General Type-2 Rule-Based Fuzzy Systems in Terms of Sculpting the State Space
    Mendel, Jerry M.
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2019, 27 (01) : 58 - 71
  • [8] A type-2 fuzzy rule-based expert system model for stock price analysis
    Zarandi, M. H. Fazel
    Rezaee, B.
    Turksen, I. B.
    Neshat, E.
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (01) : 139 - 154
  • [9] 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
  • [10] First-order rule partitions-based decomposition technique of type-1 and interval type-2 rule-based fuzzy systems for computational and memory efficiency
    El Mobaraky, Abdessamad
    Kouiss, Khalid
    Chebak, Ahmed
    [J]. INFORMATION SCIENCES, 2024, 680
12345