Electric Power Remote Monitor Anomaly Detection with a Density-Based Data Stream Clustering Algorithm
نویسندگان
چکیده
منابع مشابه
Density Based Distribute Data Stream Clustering Algorithm
To solve the problem of distributed data streams clustering, the algorithm DB-DDSC (Density-Based Distribute Data Stream Clustering) was proposed. The algorithm consisted of two stages. First presented the concept of circular-point based on the representative points and designed the iterative algorithm to find the densityconnected circular-points, then generated the local model at the remote si...
متن کاملDensity-Based Clustering and Anomaly Detection
As of 1996, when a special issue on density-based clustering was published (DBSCAN) (Ester et al., 1996), existing clustering techniques focused on two categories: partitioning methods, and hierarchical methods. Partitioning clustering attempts to break a data set into K clusters such that the partition optimizes a given criterion. Besides difficulty in choosing the proper parameter K, and inca...
متن کاملLeaDen-Stream: A Leader Density-Based Clustering Algorithm over Evolving Data Stream
Clustering evolving data streams is important to be performed in a limited time with a reasonable quality. The existing micro clustering based methods do not consider the distribution of data points inside the micro cluster. We propose LeaDen-Stream (Leader Density-based clustering algorithm over evolving data Stream
متن کاملDensity-Based Clustering over an Evolving Data Stream with Noise
Clustering is an important task in mining evolving data streams. Beside the limited memory and one-pass constraints, the nature of evolving data streams implies the following requirements for stream clustering: no assumption on the number of clusters, discovery of clusters with arbitrary shape and ability to handle outliers. While a lot of clustering algorithms for data streams have been propos...
متن کاملDG2CEP: A Density-Grid Stream Clustering Algorithm based on Complex Event Processing for Cluster Detection
Applications such as fleet and mobile task force management, or traffic control can largely benefit from the on-line detection of collective mobility patterns of vehicles, goods or persons. A common mobility pattern is a cluster, a concentration of mobile nodes in a certain region, e.g., a mass protest, a rock concert, or a traffic jam. Current approaches require previous knowledge of the locat...
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: Automation, Control and Intelligent Systems
سال: 2015
ISSN: 2328-5583
DOI: 10.11648/j.acis.20150305.12