EXPLORING THE ROLE OF GENETIC ALGORITHMS AND ARTIFICIAL NEURAL NETWORKS FOR INTERPOLATION OF ELEVATION IN GEOINFORMATION MODELS
One of the most significant tools to study many engineering projects is three-dimensional modelling of the Earth that has many applications in the Geospatial Information System (GIS), e.g. creating Digital Train Modelling (DTM). DTM has numerous applications in the fields of sciences, engineering, d...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2013-09-01
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Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-2-W1/25/2013/isprsannals-II-2-W1-25-2013.pdf |
Summary: | One of the most significant tools to study many engineering projects is three-dimensional modelling of the Earth that has many
applications in the Geospatial Information System (GIS), e.g. creating Digital Train Modelling (DTM). DTM has numerous
applications in the fields of sciences, engineering, design and various project administrations. One of the most significant events in
DTM technique is the interpolation of elevation to create a continuous surface. There are several methods for interpolation, which
have shown many results due to the environmental conditions and input data. The usual methods of interpolation used in this study
along with Genetic Algorithms (GA) have been optimised and consisting of polynomials and the Inverse Distance Weighting (IDW)
method. In this paper, the Artificial Intelligent (AI) techniques such as GA and Neural Networks (NN) are used on the samples to
optimise the interpolation methods and production of Digital Elevation Model (DEM). The aim of entire interpolation methods is to
evaluate the accuracy of interpolation methods. Universal interpolation occurs in the entire neighbouring regions can be suggested
for larger regions, which can be divided into smaller regions.
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The results obtained from applying GA and ANN individually, will be compared with the typical method of interpolation for creation
of elevations. The resulting had performed that AI methods have a high potential in the interpolation of elevations. Using artificial
networks algorithms for the interpolation and optimisation based on the IDW method with GA could be estimated the high precise
elevations. |
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ISSN: | 2194-9042 2194-9050 |