Future work can be achieved by using neuro-fuzzy systems for clustering the 3D seismic data, identification of lithofacies types, and other reservoir characterization.
Accordingly, we use Expectation Maximization (EM), Principal Component Analysis (PCA) and Adaptive Neuro-Fuzzy Inference System (ANFIS) methods for clustering, noise removal and prediction tasks, respectively.
However, existing trust systems developed for clustered WSNs are incapable of satisfying these requirements because of their high overhead and low dependability with complex global trust degree evaluation algorithms used for cluster head selection.
Docker now is building tools for launching cloud servers, systems for clustering, and a wide range of functions: building images, running images, uploading, downloading, and eventually even overlay networking, all compiled into one monolithic binary running primarily as root on your server".
We derive conditions under which clustering can take place in a general framework, and demonstrate two different behavioral regimes for clustering systems.
This tool therefore offers support for online energy management, self-healing applications, and emerging techniques for clustering power systems into adaptive self-adequate microgrids.
Pertea, G. et al. TIGR Gene Indices clustering tools (TGICL): a software system for fast clustering of large EST datasets.
In their paper, "Multisource images analysis using collaborative clustering," G. Forestier et al. propose a collaborative system for image clustering by obtaining a consensus among several clusterings that exploit heterogeneous images.
Dr. Wang's research interests include parallel architecture, software systems for Cluster and Grid computing, and virtualization techniques for Cloud computing.
