Cluster analysis of aerosol time-of-flight mass spectrometry (ATOFMS) data has been an effective tool for the identification of possible sources of ambient aerosols. In this study, the clustering results of two typical methods, adaptive resonance theory-based neural networks-2a (ART-2a) and density-based clustering of application with noise (DBSCAN), on ATOFMS data were investigated by employin...

Data mining is playing a vital role in various application fields. One important issue in data mining is clustering, which is a process of grouping data with high similarity. Density-based clustering is an effective method that can find clusters in arbitrary shapes in feature space, and DBSCAN (Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise) is a basic on...

Abstract In bearings-only localization, clustering-based methods have been widely used to remove spurious intersections by fusing multiple bearing measurements from different observation stations. Existing clustering methods, including fuzzy C-mean (FCM) and density-based spatial of applications with noise (DBSCAN), must specify the number clusters threshold for defining neighborhood density, r...

Many scientific databases nowadays are publicly available for querying and advanced data analytics. One prominent example is the Sloan Digital Sky Survey (SDSS)—SkyServer, which offers data to astronomers, scientists, and the general public. For such data it is important to understand the public focus, and trending research directions on the subject described by the database, i.e., astronomy in...

The main purpose of this paper is to achieve improvement in the speed of Fuzzy Joint Points (FJP) algorithm. Since FJP approach is a basis for fuzzy neighborhood based clustering algorithms such as Noise-Robust FJP (NRFJP) and Fuzzy Neighborhood DBSCAN (FN-DBSCAN), improving FJP algorithm would an important achievement in terms of these FJP-based methods. Although FJP has many advantages such a...

Aiming at the avian influenza outbreak in Qinghai Lake area, the satellite tracking of migratory birds in Qinghai Lake is studied to analyze the relationship between bird migration, virus spread and ecological environment. These biological problems have been converted into computational studies in previous studies in which spatial clustering is the key factor. A bird migration data analysis sys...

Cluster analysis in data mining is a main application of business. This Investigation describes to present NCDBC algorithm that extends expansion seed selection into a DBSCAN algorithm. And the DBSCAN Algorithm describes the density based clustering concept and also describes its hierarchical additional room OPTICS has been planned newly, and one of the mainly triumphant approaches to clusterin...

Tibetan information processing technology has been obtained some achievements. But it falls behind Chinese and English information processing. It still needs to be paid more attention. Text clustering has the potential to accelerate the development of Tibetan information processing. In this paper, we propose an approach of Tibetan text clustering based on machine learning. Firstly, the approach...