Combining dissimilarity matrices by using rank correlations

Amerise, Ilaria Lucrezia; Tarsitano, Agostino

doi:10.1007/s00180-015-0590-x

Cited by 4 publications

(3 citation statements)

References 18 publications

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“…To this end, the corresponding rows and columns of radial lines within Π are removed. To cluster the remaining branches using the reduced Π, Π , the dissimilarity matrix [28] needs to be obtained for Π . The dissimilarity matrix ( ) for Π is calculated as follow:…”

Section: Test System Preparationmentioning

confidence: 99%

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Negative Results on Deploying Distributed Series Reactance Devices to Improve Power System Robustness Against Cascading Failures

Beiranvand

Cuffe

2021

IEEE Trans. Power Syst.

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Distributed Series Reactances are devices that dynamically increase the impedance of a line to reduce the power flow it carries. This work explores whether widely deploying these devices enhances a power system's robustness against line overload cascading failures. The presence of Distributed Series Reactances may make it less likely that equipped lines would become overloaded by contingencies elsewhere, and so their presence may arrest the propagation of line overloads through a system. However, the efficacy of these devices in this role has not been widely investigated. Likewise, there are few extant methodologies for siting dynamic reactances within the grid to mitigate the propagation of cascades. In this paper, the ability of these devices to arrest the propagation of cascading failures within power grids is investigated. First, a novel power flow is formulated, which models dynamic line impedances. A novel methodology is proposed for siting the devices on lines spread throughout the network. With these innovations in hand, the devices' effects on cascade propagation are simulated using a sizeable database consisting of multiple load & generation snapshots across eight test networks. No major beneficial effect is found, even when 25% of lines are equipped.

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Section: Test System Preparationmentioning

confidence: 99%

“…Where is the all-ones matrix [28]: this subtraction ensures that tightly meshed lines will have low dissimilarity to each other. Then, the diagonal components in are artificially set to zero, and it is a symmetric and square matrix.…”

Section: Test System Preparationmentioning

confidence: 99%

Negative Results on Deploying Distributed Series Reactance Devices to Improve Power System Robustness Against Cascading Failures

Beiranvand

Cuffe

2021

IEEE Trans. Power Syst.

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“…() is the square of the Pearson correlation between them[3]. A value of a r,s equal zero or near zero implies that the two matrices are not linearly related, whereas a value close to one indicates a strong linear relationship between B s and B r .…”

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confidence: 99%

Multivariate Analysis of Data on Migraine Treatment

Tarsitano¹,

Amerise²

2019

ijsmr

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Migraineur constitutes a multidimensional model of health disorder involving a complex combination of genetic, psychological, demographic, enviromental and economic factors. This model provides a framework to describe limitations of an individual functional ability and quality of life, and to aid in the elaboration of more adequate intervention programs for each patient. Our primary objective in this paper is a data-driven profiling of patients. The approach followed consists of examining affinity/dissimilarity between sufferers on the basis of different family of indicators and then aggregating multiple partial matrices, where each matrix expresses a particular notion of the dissimilarity of one patient from another. One important particularity of our method is the notion of multi-dimensional dissimilarity for static and dynamic indicators, without ignoring any portion of data. The partial dissimilarity matrices are assembled in the form of a global matrix, which is used as input of subsequent calculations, such as multidimensional scaling and cluster analysis. Our main contribution is to show how multi-scale, cross-section and longitudinal data from individuals involved in a migraine treatment program may optimally be combined to allow profiling migraine-affected patients.

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