<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zagouras, A.a</style></author><author><style face="normal" font="default" size="100%">Argiriou, A.A.b</style></author><author><style face="normal" font="default" size="100%">Flocas, H.A.c</style></author><author><style face="normal" font="default" size="100%">Economou, G.a</style></author><author><style face="normal" font="default" size="100%">Fotopoulos, S.a</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An advanced method for classifying atmospheric circulation types based on prototypes connectivity graph</style></title><secondary-title><style face="normal" font="default" size="100%">Atmospheric Research</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">algorithm</style></keyword><keyword><style  face="normal" font="default" size="100%">atmospheric circulation</style></keyword><keyword><style  face="normal" font="default" size="100%">atmospheric pollution</style></keyword><keyword><style  face="normal" font="default" size="100%">Atmospheric pressure</style></keyword><keyword><style  face="normal" font="default" size="100%">Automated methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Automation</style></keyword><keyword><style  face="normal" font="default" size="100%">Classification (of information)</style></keyword><keyword><style  face="normal" font="default" size="100%">Climatology</style></keyword><keyword><style  face="normal" font="default" size="100%">Cluster analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Clustering methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Connectivity graph</style></keyword><keyword><style  face="normal" font="default" size="100%">Conventional classification methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Correlated data</style></keyword><keyword><style  face="normal" font="default" size="100%">Data sets</style></keyword><keyword><style  face="normal" font="default" size="100%">Dominant set</style></keyword><keyword><style  face="normal" font="default" size="100%">Eastern Mediterranean</style></keyword><keyword><style  face="normal" font="default" size="100%">Euclidia</style></keyword><keyword><style  face="normal" font="default" size="100%">Euclidian space</style></keyword><keyword><style  face="normal" font="default" size="100%">Fuzzy C-means algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">fuzzy mathematics</style></keyword><keyword><style  face="normal" font="default" size="100%">geopotential</style></keyword><keyword><style  face="normal" font="default" size="100%">Geopotential height</style></keyword><keyword><style  face="normal" font="default" size="100%">Graph clustering</style></keyword><keyword><style  face="normal" font="default" size="100%">Graph formulations</style></keyword><keyword><style  face="normal" font="default" size="100%">Graph theory</style></keyword><keyword><style  face="normal" font="default" size="100%">graphical method</style></keyword><keyword><style  face="normal" font="default" size="100%">Manual classification</style></keyword><keyword><style  face="normal" font="default" size="100%">MAP classification</style></keyword><keyword><style  face="normal" font="default" size="100%">Mathematical approach</style></keyword><keyword><style  face="normal" font="default" size="100%">Mediterranean Region</style></keyword><keyword><style  face="normal" font="default" size="100%">Methodological tools</style></keyword><keyword><style  face="normal" font="default" size="100%">Perceptual experience</style></keyword><keyword><style  face="normal" font="default" size="100%">Prototype selection</style></keyword><keyword><style  face="normal" font="default" size="100%">spatial data</style></keyword><keyword><style  face="normal" font="default" size="100%">Variable number of clusters</style></keyword><keyword><style  face="normal" font="default" size="100%">Weather maps</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.scopus.com/inward/record.url?eid=2-s2.0-84863741960&amp;partnerID=40&amp;md5=d4ebee969cafbc2bc61bbc59300856b4</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">118</style></volume><pages><style face="normal" font="default" size="100%">180-192</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Classification of weather maps at various isobaric levels as a methodological tool is used in several problems related to meteorology, climatology, atmospheric pollution and to other fields for many years. Initially the classification was performed manually. The criteria used by the person performing the classification are features of isobars or isopleths of geopotential height, depending on the type of maps to be classified. Although manual classifications integrate the perceptual experience and other unquantifiable qualities of the meteorology specialists involved, these are typically subjective and time consuming. Furthermore, during the last years different approaches of automated methods for atmospheric circulation classification have been proposed, which present automated and so-called objective classifications. In this paper a new method of atmospheric circulation classification of isobaric maps is presented. The method is based on graph theory. It starts with an intelligent prototype selection using an over-partitioning mode of fuzzy c-means (FCM) algorithm, proceeds to a graph formulation for the entire dataset and produces the clusters based on the contemporary dominant sets clustering method. Graph theory is a novel mathematical approach, allowing a more efficient representation of spatially correlated data, compared to the classical Euclidian space representation approaches, used in conventional classification methods. The method has been applied to the classification of 850. hPa atmospheric circulation over the Eastern Mediterranean. The evaluation of the automated methods is performed by statistical indexes; results indicate that the classification is adequately comparable with other state-of-the-art automated map classification methods, for a variable number of clusters. © 2012 Elsevier B.V.</style></abstract><notes><style face="normal" font="default" size="100%">cited By (since 1996)1</style></notes></record></records></xml>