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<!-- Dissertationen grundsätzlich mit der folgenden Vorlage "diss" erstellen! -->
{{disskatinst|Universität|Koblenz-Landau}}
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{{diss
| name= Ralf, Wagner              <!-- Name der Autorin/des Autors -->
| titel = Components of a Spatial-Toolbox for processing geocoded mapping information in the context of decision support                        <!-- Titel der Dissertation (gleich dem Seitennamen) -->
| hochschule= Universität Koblenz-Landau  <!-- Name der Hochschule -->
| jahr = 2010                                                    <!-- Jahr der Promotion -->
| betreut1 =  Prof.Dr.Engelbert Niehaus                                          <!-- Erstbetreuer/in -->
| betreut2 =                                            <!-- Zweitbetreuer/in -->
| begutachtet1 =  Prof.Dr.Engelbert Niehaus (Universität Koblenz-Landau)                                  <!-- Erstgutachter/in -->
| begutachtet2 =  Prof.Dr.Dr.Marlien Herselman (Nelson Mandela Metropolitan University, Port Elizabeth and George, Südafrika)                                  <!-- Zweitgutachter/in -->
| begutachtet3 =                                    <!-- ggf. Drittgutacher/in -->
| download =  http://kola.opus.hbz-nrw.de/volltexte/2010/539/                                          <!-- Download-URL (inkl. http://) -->
| sprache =  Englisch                                            <!-- Nur ausfüllen, falls nicht Deutsch -->
| note =                                                <!-- in Worten oder Zahlen -->
| pruefungam = 23.08.2010                                      <!-- Datum der mündlichen Prüfung in Form 25.12.2009 -->
| schulart =                                                <!-- Hauptschule, Realschule, ... -->
| stufe =                                                      <!-- Primarstufe, Sekundarstufe 1, Sekundarstufe 2, ... -->
}}
== Zusammenfassung ==
<!-- Hier bitte eine Zusammenfassung der Dissertation einfügen.
          Zwischenüberschriften mit === ... === kennzeichnen. -->
 
 
This  dissertation provides an interdisciplinary contribution to the project  ReGLaN-Health & Logistics. ReGLaN-Health & Logistics, is an  international cooperation deriving benefits from the capabilities of  scientists working on different fields. The aim of the project is the  development of a so-called SDSS that supports decision makers working  within health systems with a special focus on rural areas. In this  dissertation, one important component for the development of the DSS  named EWARS is proposed and described in detail. This component called  SPATTB is developed with the intention of dealing with spatial data,  i.e. data with additional geocoded information with regard to the  special requirements of the EWARS.rnrnAn important component in the  process of developing the EWARS is the concept of GIS. Classically,  geocoded information with a vectorial character numerically describing  spatial phenomena is managed and processed in a GIS. For the development  of the EWARS, the manageability of the type of data exemplarily given  by (x,y,o) with coordinates x,y ) and Ozon-concentration o is not  sufficient. It is described, that the manageable data has to be extended  to data of type (x,y,f ), where (x,y) are the geocoded information, but  where f is not only a numerical value but a functional description of a  certain phenomenom. An example for the existence and appearance of that  type of data is the geocoded information about the variation of the  Ozon-concentration in time or depending on temperature. A knowledge-base  as important subsystem of DSS containing expert knowledge is mentioned.  This expert-knowledge can be made manageable when using methods from  the field of fuzzy logic. Thereby mappings, so-called fuzzy-sets, are  generated. Within the EWARS, these mappings will be used with respect to  additional geocoded data. The knowledge about the geocoded mapping  information only at a finite set of locations (x,y) associated with  mapping information f is not sufficient in applications that need  continuous statements in a certain geographical area. To provide a  contribution towards solving this problem, methods from the field of  computer geometry and CAD, so-called Bezier-methods, are used for  interpolating this geocoded mapping information. Classically, these  methods operates on vectors a the multidimensional vector-space whose  elements contain real-valued components but in terms of dealing with  mapping information, there has to be an extension on topological vector  spaces since mapping spaces can be defined as such spaces. This builds a  new perspective and possibility in the application of these methods.  Therefore, the according algorithms have to be extended; this work is  presented.rnrnThe field of Artificial Neural Networks plays an important  role for the processing and management of the data within the EWARS,  where features of biological processes and structures are modeled and  implemented as algorithms. Generally, the developed methods can be  divided as usable in terms of interpolation or approximation functional  coherences and in such being applicable to classification problems. In  this dissertation one method from each type is regarded in more  detailed. Thereby, the classical algorithms of the so-called  Backpropagation-Networks for approximation and the Kohonen-Networks for  classification are described.  Within the thesis, an extension of these  algorithms is then proposed using coherences from mathematical  measure-theory and approximation theory. The mentioned extension of  these algorithms is based on a preprocessing of the mapping data using  integration methods from measure theory.
 
 
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== Schlagworte ==
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Beispiele:
[[Dynamische Geometrie]],  [[DGS]] -->
 
[[Bézier-Curve]] [[Bézier-Surface]] [[Decision-support]] [[Networks]] [[Mapping]] [[Measure-theory]] [[Artificial Neural Networks ]]
 
 
<!-- == Kontext == -->
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<!-- === Literatur === -->
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<!-- == Diskussion == -->
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Aktuelle Version vom 28. Juni 2012, 15:22 Uhr


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