2006 International Symposium on Evolving Fuzzy Systems最新文献_第6页

Non-Parametric Model Structure Identification and Parametric Efficiency in Nonlinear State Dependent Parameter Models 非线性状态依赖参数模型的非参数模型结构辨识与参数效率

2006 International Symposium on Evolving Fuzzy Systems Pub Date : 2006-11-30 DOI: 10.1109/ISEFS.2006.251137

P. Young

引用次数: 7

Novelty Detection Based Machine Health Prognostics 基于机器健康预测的新颖性检测

2006 International Symposium on Evolving Fuzzy Systems Pub Date : 2006-11-30 DOI: 10.1109/ISEFS.2006.251161

Dimitar Filev, F. Tseng

引用次数: 49

Generation of Fuzzy Classification Rules by Non-Overlapping Input Partitioning 基于非重叠输入划分的模糊分类规则生成

2006 International Symposium on Evolving Fuzzy Systems Pub Date : 2006-11-30 DOI: 10.1109/ISEFS.2006.251146

L. Mikhailov

引用次数: 3

Evolving Fuzzy Systems from Data Streams in Real-Time 实时数据流演化模糊系统

2006 International Symposium on Evolving Fuzzy Systems Pub Date : 2006-09-07 DOI: 10.1109/ISEFS.2006.251157

P. Angelov, Xiaowei Zhou

{"title":"Evolving Fuzzy Systems from Data Streams in Real-Time","authors":"P. Angelov, Xiaowei Zhou","doi":"10.1109/ISEFS.2006.251157","DOIUrl":"https://doi.org/10.1109/ISEFS.2006.251157","url":null,"abstract":"An approach to real-time generation of fuzzy rule-base systems of extended Takagi-Sugeno (xTS) type from data streams is proposed in the paper. The xTS fuzzy system combines both zero and first order Takagi-Sugeno (TS) type systems. The fuzzy rule-base (system structure) evolves starting 'from scratch' based on the data distribution in the joint input/output data space. An incremental clustering procedure that takes into account the non-stationary nature of the data pattern and generates clusters that are used to form fuzzy rule based systems antecedent part in on-line mode is used as a first stage of the non-iterative learning process. This structure proved to be computationally efficient and powerful to represent in a transparent way complex non-linear relationships. The decoupling of the learning task into a non-iterative, recursive (thus computationally very efficient and applicable in real-time) clustering with a modified version of the well known recursive parameter estimation technique leads to a very powerful construct - evolving xTS (exTS). It is transparent and linguistically interpretable. The contributions of this paper are: i) introduction of an adaptive recursively updated radius of the clusters (zone of influence of the fuzzy rules) that learns the data distribution/variance/scatter in each cluster; ii) a new condition to replace clusters that excludes contradictory rules; iii) an extended formulation that includes both zero order TS and simplified Mamdani multi-input-multi-output (MIMO) systems; iv) new improved formulation of the membership functions, which closer resembles the normal Gaussian distribution; v) introduction of measures of clusters quality that are used to form the antecedent parts of respective fuzzy rules, namely their age and support; vi) experimental results with a well known benchmark problem as well as with real experimental data of concentration of exhaust gases (NOx) in on-line modeling of car engine test rigs","PeriodicalId":269492,"journal":{"name":"2006 International Symposium on Evolving Fuzzy Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2006-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124192699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 243