Napovedovanje premikov pri plazenju tal z umetnimi nevronskimi mrežami RBF

diplomska naloga

Matjaž Mlakar (Author), Tomaž Ambrožič (Mentor), Dušan Kogoj (Thesis defence commission member), Radoš Šumrada (Thesis defence commission member), Janko Logar (Co-mentor)

Abstract

Keywords

geodezija;diplomska dela;UNI;Macesnikov plaz;umetna nevronska mreža;RBF;geodetske meritve;premiki;padavine;analiza;

Data

Language:	Slovenian
Year of publishing:	2011
Source:	Ljubljana
Typology:	2.11 - Undergraduate Thesis
Organization:	UL FGG - Faculty of Civil and Geodetic Engineering
Publisher:	[M. Mlakar]
UDC:	004:624.131.5(043.2)
COBISS:	5247841
Views:	5202
Downloads:	532
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	ǂThe ǂprediction of landslide movements with RBF artificial neural networks
Secondary abstract:	The thesis deals with the problem of the prediction of landslide movements with artificial neural networks (ANN). Landslide movements are dependent on many parameters (rainfall, topography, geology, material, ...), what makes them hard to predict. The links between movements, rainfall, temperature and surface inkilnation are too complex to define them with mathematical equations. That is why we use artificial neural networks. In the beginning we describe the Macesnik landslide, where the observations took place. We continue with the description of previous observations on the Macesnik landslide and we analyze the influence of rainfall on movements of the landslide. Next, we describe artificial neural networks, distribution of the artificial neural networks, the criteria of distributing artificial neural networks and present a detail description of the radial basis function (RBF) neural networks. In the experimental part we have presented the use of artificial neural networks for the prediction of landslide movements. For input and output data we have used the measurements of rainfall and measured movements of the landslide, respectively. Our goal is to find a artificial neural network, which could be used for landslide movement prediction in the future. For the calculation we used two different sotwares – Matlab R2007b and Neurosolutions. At the end conclusions are given, which include a short summary of all major findings.
Secondary keywords:	graduation thesis;geodesy;Macesnik's;landslides;artificial neural network;RBF;geodetic measurements;movements;rainfall;analysis;
File type:	application/pdf
Type (COBISS):	Undergraduate thesis
Thesis comment:	Univ. v Ljubljani, Fak. za gradbeništvo in geodezijo
Pages:	XII, 80 str., [4] pril.
Type (ePrints):	thesis
Title (ePrints):	The prediction of landslide movements with RBF artificial neural networks
Keywords (ePrints):	Macesnikov plaz;umetna nevronska mreža;RBF;geodetske meritve;premiki;padavine;analiza
Keywords (ePrints, secondary language):	Macesnik’s landslide;artificial neural network;RBF;geodetic measurements;movements;rainfall;analysis
Abstract (ePrints):	Diplomska naloga predstavlja možnost uporabe umetnih nevronskih mrež pri napovedovanju premikov pri plazenju tal. Premiki plazov so odvisni od mnogih dejavnikov (padavine, topografija, geologija, materialne lastnosti, …), zato jih je težko napovedati. Povezave med premiki, padavinami, temperaturami in inklinacijo terena so preveč kompleksne, da bi jih opisali z matematičnimi formulami. Zato jih poskusimo opisati z umetnimi nevronskimi mrežami. V nalogi najprej predstavimo Macesnikov plaz, kjer so bile izvedene meritve. V nadaljevanju opišemo dosedanja opazovanja Macesnikovega plazu in analiziramo vpliv padavin na plazenje zemljin. Sledi predstavitev umetnih nevronskih mrež, razdelitev umetnih nevronskih mrež, kriteriji razdelitve umetnih nevronskih mrež in podrobna razložitev radialnih bazičnih umetnih nevronskih mrež. V eksperimentalnem delu je prikazana uporaba radialnih bazičnih umetnih nevronskih mrež pri napovedovanju plazenja zemljin. Za vhodne podatke smo uporabili meritve padavin, za izhodne pa premike plazenja zemljine. Cilj je dobiti naučeno umetno nevronsko mrežo, ki bi jo lahko uporabili za napovedovanje premikov v praksi. Za izračun uporabimo dve različni programski opremi – Matlab R2007b in Neurosolutions, katerih rezultate primerjamo med seboj. Na koncu podamo zaključek, ki vsebuje kratek povzetek vseh glavnih ugotovitev.
Abstract (ePrints, secondary language):	The thesis deals with the problem of the prediction of landslide movements with artificial neural networks (ANN). Landslide movements are dependent on many parameters (rainfall, topography, geology, material, ...), what makes them hard to predict. The links between movements, rainfall, temperature and surface inkilnation are too complex to define them with mathematical equations. That is why we use artificial neural networks. In the beginning we describe the Macesnik landslide, where the observations took place. We continue with the description of previous observations on the Macesnik landslide and we analyze the influence of rainfall on movements of the landslide. Next, we describe artificial neural networks, distribution of the artificial neural networks, the criteria of distributing artificial neural networks and present a detail description of the radial basis function (RBF) neural networks. In the experimental part we have presented the use of artificial neural networks for the prediction of landslide movements. For input and output data we have used the measurements of rainfall and measured movements of the landslide, respectively. Our goal is to find a artificial neural network, which could be used for landslide movement prediction in the future. For the calculation we used two different sotwares – Matlab R2007b and Neurosolutions. At the end conclusions are given, which include a short summary of all major findings.
Keywords (ePrints, secondary language):	Macesnik’s landslide;artificial neural network;RBF;geodetic measurements;movements;rainfall;analysis
ID:	8312117