Partial Order Concepts in Applied Sciences

Partial Order Concepts in Applied Sciences

Bruggemann, Rainer; Fattore, Marco

Springer International Publishing AG

12/2016

307

Dura

Inglês

9783319454191

15 a 20 dias

6033


ebook

Descrição não disponível.
Part I.Theoretical and methodological advances.- 1.Endowing posets with flesh: if, why and how?.- 2.Incomparability/inequality measures and clustering.- 3.Incomparable - what now, IV. Incomparabilities - a modeling challenge.- 4.Partial Ordering and Metrology Analyzing Analytical Performance.- 5.Functionals and synthetic indicators over finite posets.-6.Evaluation, considered as problem orientable mathematics over lattices.- 7.A combined lexicographic-average rank approach for evaluating uncertain multi-indicator matrices with risk metrics.- Part II.Partial Order Theory in socio-economic sciences.- 8.Peculiarities in multidimensional regional poverty.- 9.Application of Partial Order Theory to Multidimensional Poverty Analysis in Switzerland.- 10.Analysis of social participation: a multidimensional approach based on the theory of partial ordering.- 11.POSET analysis of panel data with POSAC.- 12.Partially Ordered SetTheory and Sen's capability approach: a fruitful relationship.- Part III.Partial Order Theory in environmental sciences.- 13.Ranking Chemicals with Respect to Accidents Frequency.- 14.Formal Concept Analysis applications in chemistry: from radionuclides and molecular structure to toxicity and diagnosis.- 15.Partial Order Analysis of the government dependence of the Sustainable Development Performance in Germany?s Federal States.- Part IV.New applications of Partial Order Theory.- 16.A matching problem, partial order and an analysis applying the Copeland index.- 17.Application of the Mixing Partial Order to Genes.- 18.Analysing ethnopharmacological data matrices on traditional uses of medicinal plants with the contribution of Partial Order Techniques.- Part V.Software developments.- 19.PARSEC: An R package for partial orders in socio-economics.- 20.PyHasse and cloud computing.


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Hasse diagrams;data analysis;multi-criteria desicion making;multi-indicator systems;partial order