Application of SOM neural network in clustering
نویسندگان
چکیده
منابع مشابه
Application of SOM neural network in clustering
The Self-Organizing Map (SOM) is an unsupervised neural network algorithm that projects high-dimensional data onto a two-dimensional map. The projection preserves the topology of the data so that similar data items will be mapped to nearby locations on the map. One of the SOM neural network’s applications is clustering of animals due their features. In this paper we produce an experiment to ana...
متن کاملFuzzy Association Rule Reduction Using Clustering In Som Neural Network
The major drawback of fuzzy data mining is that after applying fuzzy data mining on the quantitative data, the number of extracted fuzzy association rules is very huge. When many association rules are obtained, the usefulness of them will be reduced. In this paper, we introduce an approach to reduce and summarize the extracted fuzzy association rules after fuzzy data mining. In our approach, in...
متن کاملusing som neural network in text information retrieval
with the increase of the volume of information and the progress in technology, the deficiency of traditional algorithms for fast information retrieval becomes more clear. when large volumes of data are to be handled, the use of neural network as an artificial intelligent technique is a suitable method to increase the information retrieval speed. neural networks present a suitable representation...
متن کاملApplication of Fuzzy Clustering Neural Network in Conjunction Speech Recognition
In order to improve the approximation property of the past fuzzy clustering algorithms when identifying systems, a fuzzy clustering neural network (FCNN) is proposed and is applied to conjunction speech recognition system. Based on the fuzzy system model, FCNN presents every state as a fuzzy system and uses continuous frames as the system input. With improving fuzzy clustering identification al...
متن کاملComparing SOM neural network with Fuzzy c
In this paper we present a comparison among some nonhierarchical and hierarchical clustering algorithms including SOM (Self-Organization Map) neural network and Fuzzy c-means methods. Data were simulated considering correlated and uncorrelated variables, nonoverlapping and overlapping clusters with and without outliers. A total of 2530 data sets were simulated. The results showed that Fuzzy c-m...
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: Journal of Biomedical Science and Engineering
سال: 2009
ISSN: 1937-6871,1937-688X
DOI: 10.4236/jbise.2009.28093