Large-scale atmospheric circulation patterns are the primary drivers of wind power variability on networks at timescales hours to days. This paper proposes a methodology that allows system operators and planners working with high levels generation, conduct probabilistic flow (PPF) analyses by defining network ‘operating scenarios’ – i.e. probability density functions generators, correlations be...

Recent work has shown that the node degree in the WWW induced graph and the AS-level Internet topology exhibit power laws. Since then several algorithms have been proposed to generate such power law graphs. In this paper we evaluate the effectiveness of these generators to generate representative AS-level topologies. Our conclusions are mixed. Although they (mostly) do a reasonable job at captu...

permanent magnet synchronous generators (pmsgs) are novel generators which can be used in high-performance wind farms. high efficiency and flexibility in producing electricity from variable rotation make them good candidate for wind power applications. furthermore, because these kinds of generators have no excitation winding, there is no copper loss on rotor; hence, they can operate at high pow...

This paper presents a further investigation into computational properties of a novel fuzzy additive spectral clustering method, FADDIS, recently introduced by authors (Mirkin and Nascimento 2012). Specifically, we extend our analysis to “difficult” data structures from the recent literature and develop two synthetic data generators simulating affinity data of Gaussian clusters and genuine addit...

The quality of clustering algorithms is often based on their performance according to a specific quality index, in an experimental evaluation. Experiments either use a limited number of real-world instances or synthetic data. While real-world data is crucial for testing such algorithms, it is scarcely available and thus insufficient. Therefore, synthetic pre-clustered data has to be assembled a...

Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Although abundant expert knowledge exists in many areas where unlabelled data is examined, frequently such knowledge is not incorporated into automatic analysis. Semi-supervised learning allows for the incorporation of additional knowledge with the help of labels or constraints. However ...

MOTIVATION Various clustering methods have been applied to microarray gene expression data for identifying genes with similar expression profiles. As the biological annotation data accumulated, more and more genes have been organized into functional categories. Functionally related genes may be regulated by common cellular signals, thus likely to be co-expressed. Consequently, utilizing the rap...

Objective type of Examination evaluation is easy in Computer world. But the descriptive type of question evaluation is more difficult and there is no significant research has been taken place. In this paper I propose a new solution to the above problem with text classification using the new fuzzy logic named CosFuzzy Logic. Document Clustering is a useful technique that organizes a large quanti...

The topology of a network (connectivity of autonomous systems (ASes) or routers) has significant implications on the design of protocols and applications, and on the placement of services and data centers. Researchers and practitioners alike are in constant need of realistic topologies for their simulation, emulation, and testbed experiments. In this work, we propose a multi-level framework for...