Hybrid learning-based neuro-fuzzy inference system: a new approach for system modeling

被引:9
|
作者
Cheng, K. -H. [1 ]
机构
[1] Ind Technol Res Inst, Mech & Syst Res Labs, Hsinchu 310, Taiwan
关键词
fuzzy inference; hybrid learning; system modeling; time series identification and prediction;
D O I
10.1080/00207720701747465
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 article, a hybrid learning neuro-fuzzy inference system (HLNFIS) with a new inference mechanism is proposed for system modeling. In the HLNFIS, the incoming signal is fuzzified by the proposed improved Gaussian membership function (IGMF), which is derived from two standard Gaussian functions. With the premise construction with IGMFs, the system inference ability can be upgraded. The fuzzy inference processor, which involves both numerical and linguistic reasoning, is introduced in rule base construction. For effective parameter learning, the hybrid algorithm of random optimization (RO) and least square estimation (LSE) is exploited, where the premise and the consequence parameters of are updated by RO and LSE, respectively. To validate the feasibility and the potential of the proposed approach, three examples of system modeling are conducted. Through experimental results and comparisons the proposed HLNFIS shows excellent performance for complex modeling.
引用
收藏
页码:583 / 600
页数:18
相关论文
共 50 条
  • [41] An Adaptive Neuro-Fuzzy Inference System Based Approach to Real Estate Property Assessment
    Guan, Jian
    Zurada, Jozef
    Levitan, Alan S.
    JOURNAL OF REAL ESTATE RESEARCH, 2008, 30 (04) : 395 - 421
  • [42] A Predictive Visual Analytics Evaluation Approach Based on Adaptive Neuro-Fuzzy Inference System
    Amri, Saber
    Ltifi, Hela
    Ben Ayed, Mounir
    COMPUTER JOURNAL, 2019, 62 (07): : 977 - 1000
  • [43] ADAPTIVE METHOD OF HYBRID LEARNING FOR AN EVOLVING NEURO-FUZZY SYSTEM
    Bodyanskiy, Ye. V.
    Boiko, O. O.
    Pliss, I. P.
    CYBERNETICS AND SYSTEMS ANALYSIS, 2015, 51 (04) : 500 - 505
  • [44] Modelling of an agricultural robot applying Neuro-Fuzzy inference system approach
    Xie, Jun
    Xu, Xinying
    Xie, Keming
    2007 IEEE INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION, VOLS 1-7, 2007, : 568 - 571
  • [45] A new hybrid intelligent path planner for mobile robot navigation based on adaptive neuro-fuzzy inference system
    Mohanty, Prases K.
    Parhi, Dayal R.
    AUSTRALIAN JOURNAL OF MECHANICAL ENGINEERING, 2015, 13 (03) : 195 - 207
  • [46] An optimization of a planning information system using fuzzy inference system and adaptive neuro-Fuzzy inference system
    1600, World Scientific and Engineering Academy and Society, Ag. Ioannou Theologou 17-23, Zographou, Athens, 15773, Greece (10):
  • [47] Bayesian inference using an adaptive neuro-fuzzy inference system
    Knaiber, Mohammed
    Alawieh, Leen
    FUZZY SETS AND SYSTEMS, 2023, 459 : 43 - 66
  • [48] RETRACTED ARTICLE: Hybrid Recommendation System for Heart Disease Diagnosis based on Multiple Kernel Learning with Adaptive Neuro-Fuzzy Inference System
    Gunasekaran Manogaran
    R. Varatharajan
    M. K. Priyan
    Multimedia Tools and Applications, 2018, 77 : 4379 - 4399
  • [49] Retraction Note: Hybrid recommendation system for heart disease diagnosis based on multiple kernel learning with adaptive neuro-fuzzy inference system
    Gunasekaran Manogaran
    R. Varatharajan
    M. K. Priyan
    Multimedia Tools and Applications, 2023, 82 : 3181 - 3181
  • [50] Neuro-fuzzy modeling approach to gas turbine dynamic system
    Kim, SK
    Fleming, PJ
    Thompson, H
    INTELLIGENT CONTROL SYSTEMS AND SIGNAL PROCESSING 2003, 2003, : 493 - 498