kEFCM: kNN-Based Dynamic Evolving Fuzzy Clustering Method
نویسندگان
چکیده
منابع مشابه
kEFCM: kNN-Based Dynamic Evolving Fuzzy Clustering Method
Despite the recent emergence of research, creating an evolving fuzzy clustering method that intelligently copes with huge amount of data streams in the present high-speed networks involves a lot of difficulties. Several efforts have been devoted to enhance traditional clustering techniques into on-line evolving fuzzy able to learn and develop continuously. In line with these efforts, we propose...
متن کاملA new ensemble clustering method based on fuzzy cmeans clustering while maintaining diversity in ensemble
An ensemble clustering has been considered as one of the research approaches in data mining, pattern recognition, machine learning and artificial intelligence over the last decade. In clustering, the combination first produces several bases clustering, and then, for their aggregation, a function is used to create a final cluster that is as similar as possible to all the cluster bundles. The inp...
متن کاملA Hybrid Time Series Clustering Method Based on Fuzzy C-Means Algorithm: An Agreement Based Clustering Approach
In recent years, the advancement of information gathering technologies such as GPS and GSM networks have led to huge complex datasets such as time series and trajectories. As a result it is essential to use appropriate methods to analyze the produced large raw datasets. Extracting useful information from large data sets has always been one of the most important challenges in different sciences,...
متن کاملFuzzy Clustering Method for Content-based Indexing
E cient and accurate information retrieval is one of the main issues in multimedia databases. In content-based multimedia retrieval databases, contents or features of the database objects are used for retrieval. To retrieve similar database objects, we often perform a nearest-neighbor search. A nearest-neighbor search is used to retrieve similar database objects with features nearest to the que...
متن کاملA Clustering-Based Method for Fuzzy Modeling
In this paper, a clustering-based method is proposed for automatically constructing a multi-input TakagiSugeno (TS) fuzzy model where only the input-output data of the identified system are available. The TS fuzzy model is automatically generated by the process of structure identification and parameter identification. In the structure identification step, a clustering method is proposed to prov...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Advanced Computer Science and Applications
سال: 2015
ISSN: 2156-5570,2158-107X
DOI: 10.14569/ijacsa.2015.060202