Utilização de redes neurais na determinação de modelos geoidais / Using artificial neural network to obtain geoid models.

AUTOR(ES)

Túle Cesar Barcelos Maia

DATA DE PUBLICAÇÃO

2003

RESUMO

Applying data from EGM96 geopotential model, gravimetric, GPS and geometric leveling data and using spherical harmonics and FFT as techniques of geoidal determination, this thesis has the goal to find a fast alternative tool to define a geoidal undulation model considering precision and a small effort to estimate important parameters to obtain the mentioned model. MLP neural networks, backpropagation algorithm changing the numbers of layers, neurons numbers, activation function, learning rate and momentum term have been applied. The data of the mentioned models were handling aiming to be used by the neural networks models. Normalization, analysis of the main components, definition of the input and output attributes to training the neural network model, have been also used. Comparison among existing models and the models used in this research with results obtained by the neural network have been done, showing the errors between the created surfaces. At the end, it is presented a positive argument to use the MLP neural network to generate a geoidal model with advantages and disadvantages.

ASSUNTO(S)

fft geoidal ondulation gravimetry neural networks ondulaçõa geoidal redes gps fft geóide gps network pca pca geoid geopotencial model modelo geopotencial gravimetria redes neurais

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