Supporting the Process of Monument Classification Based on Reducts, Decision Rules and Neural Networks

被引：0

作者：

Olszewski, Robert ^{[1
]}

Fiedukowicz, Anna ^{[1
]}

机构：

[1] Warsaw Univ Technol, Fac Geodesy & Cartog, Dept Cartog, Warsaw, Poland

来源：

ROUGH SETS AND INTELLIGENT SYSTEMS PARADIGMS, RSEISP 2014 | 2014年 / 8537卷

关键词：

rough sets; neural networks; spatial data mining; multi-characteristic spatial data; classification;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The present article attempts to support the process of classification of multi-characteristic spatial data in order to develop the correct cartographic visualisation of complex geographical information in the thematic geoportal. Rough sets, decision rules and artificial neural networks were selected as relevant methods of spatially distributed monument classification. Basing on the obtained results it was determined that the attributes reflecting the spatial relations between specific objects play an extremely significant role in the process of classification, reducts allow to select exclusively essential attributes of objects and neural networks and decision rules are highly useful for the purposes of classification of multi-characteristic spatial data.

引用

页码：327 / 334

页数：8

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