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The current study presents an image segmentation algorithm based on modified FCM. One of the main image characteristics is the correlation between neighboring pixels. In other words, in the image segmentation, neighboring pixels are likely to belong to the same cluster. In conventional FCM, cluster assignment is only based on pixels attributes and the way they are distributed, and at the same time...
The traditional water consumption models were mainly focused on the spatial scale of city or district, on the time scale of year or month, and with data precision of 0.1 m3. As the Internet of Thing (IoT) technology develops rapidly, the smart meters for water-supply are gradually popularized. In the year 2013, Guangzhou City of China established a demonstration area of smart water-supply, in which...
Financial crisis is the most significant and comprehensive performance of enterprise crisis. From the empirical point of view, this paper sets up a financial evaluation index set for enterprise financial crisis. First, in-depth analysis of various financial indicators of listed companies is made to choose related index. Then taking all the listed companies as samples, fuzzy clustering is used to clustering...
With the boom of web and social networking, the amount of generated text data has increased enormously. Much of this data can be considered and modeled as a stream and the volume of such data necessitates the application of automated text classification strategies. Although streaming data classification is not new, considering text data streams for classification purposes has been extensively researched...
This paper proposes a new method for selecting input variables in short-term electric load forecasting models. It is known that input and output variables do not follow the Gaussian distribution in load forecasting. In this paper, a hybrid method of graphical modeling (GM) and deterministic annealing EM (DAEM) clustering is presented to clarify causal relationship between the explained one-step-ahead...
In multi-sensor and multi-target nomadic tracking systems, for making decision, signals with noise as input must be sent to fusion center to be filtered, associated, combined and made final decision as output. In the chain, association is very important processing. In this paper, an efficient fuzzy logic data association approach for nomadic tracking systems is studied. The proposed approach is developed...
As a non-parametric algorithm, empirical copula is an effective way to estimate the dependence structure of high-dimension arbitrarily distributed data. However, it suffers from the problem of huge computation time because of its high computational complexity. In this paper, fuzzy empirical copula is proposed to solve this problem by combining the fuzzy clustering by local approximation of memberships...
For expressing the fuzziness and uncertainty of domain knowledge, realizing the semantic retrieval of fuzzy information, this paper produces an extended fuzzy ontology model and proposes a kind of semantic query expansion technology which can implement semantic information query based on the property values and the relationships of fuzzy concepts. The extended fuzzy ontology provides appropriate support...
The algorithm of locally adaptive clustering for high dimensional data (LAC) processes soft subspace clustering by local weightings of features. To solve the localization of LAC in specifying the number of clusters, this paper reworks the validity index for fuzzy clustering to evaluate the clustering results of LAC. Compared with real clustered data, the method is proved feasible. In the new algorithm,...
It is very difficult to obtain labeled training samples. However, it is very easy to obtain non-labeled training samples. So,it is important task that how to classify Web-page using these training samples. An Algorithm called FC-TSVM based on fuzzy clustering is proposed. The algorithm FC-TSVM uses the fuzzy clustering algorithm to determine the number of positive label samples, and add the information...
Personalized recommendation systems can help people to find interesting things and they are widely used in our life. Poor quality is one major challenge in collaborative filtering recommender systems. Sparsity of source data set is the major reason causing the poor quality. Aiming at the problem of data sparsity for collaborative filtering, a novel rough set and fuzzy clustering based collaborative...
Collaborative filtering technique has been proved to be one of the most successful techniques in recommendation systems in recent years. However, most existing collaborative filtering based recommendation systems suffered from its shortage in scalability as their calculation complexity increased quickly both in time and space when the record in user database increases. So, a new collaborative filtering...
For the purpose of reducing redundant alerts and false alerts as well as recognizing complicated attack scenarios, a multilevel model of alert fusion is presented. This model fuses alerts layer upon layer through primary alert reduction, alert verification, alert clustering and alert correlation. In order to construct accurate and complete attack sensors, in the phase of alert clustering, this paper...
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