The increasing complexity of Internet of Things and modern battlefield electromagnetic environments poses significant challenges to radiation source localization, especially under electronic ...

1 Tianjin University of Technology and Education, Tianjin, China. 2 Lvliang Vocational and Technical College, Lvliang, China. In modern society, dense crowd detection technology is particularly ...

A good way to see where this article is headed is to take a look at the screenshot in Figure 1 and the graph in Figure 2. The demo program begins by loading a tiny 10-item dataset into memory. The ...

Clustering methods in Machine Learning includes both theory and python code of each algorithm. Algorithms include K Mean, K Mode, Hierarchical, DB Scan and Gaussian Mixture Model GMM. Interview ...

working with amazons3 ,t2.micro Ubuntu instance, Amazon AutoScaling group, Map-Reduce and Parallelize the implementation of K-means and DBSCAN algorithm using Hadoop and Map reduce cluster ...

Abstract: With the explosive growth of data, we have entered the era of big data. In order to sift through masses of information, many data mining algorithms using parallelization are being ...

Abstract: DBSCAN is a well-known clustering algorithm which is based on density and is able to identify arbitrary shaped clusters and eliminate noise data. However, parallelization of DBSCAN is a ...

ABSTRACT: Genetic algorithms have been extensively used as a global optimization tool. These algorithms, however, suffer from their generally slow convergence rates. This paper proposes two approaches ...