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Serena Moretto, Francesca Bozzano, Carlo Esposito, Paolo Mazzanti and Alfredo Rocca
In this work, the ability of advanced satellite interferometry to monitor pre-failure landslide behaviours and the potential application of this technique to Failure Forecasting Methods (FFMs) are analysed. Several limits affect the ability of the techni...
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Pablo de Llano, Carlos Piñeiro, Manuel Rodríguez
Pág. pp. 163 - 198
This paper offers a comparative analysis of the effectiveness of eight popular forecasting methods: univariate, linear, discriminate and logit regression; recursive partitioning, rough sets, artificial neural networks, and DEA. Our goals are: clarify the...
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Pablo de Llano, Carlos Piñeiro, Manuel Rodríguez
Pág. pp. 163 - 198
This paper offers a comparative analysis of the effectiveness of eight popular forecasting methods: univariate, linear, discriminate and logit regression; recursive partitioning, rough sets, artificial neural networks, and DEA. Our goals are: clarify the...
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Guoqi Qian, Antoinette Tordesillas and Hangfei Zheng
High-dimensional, non-stationary vector time-series data are often seen in ground motion monitoring of geo-hazard events, e.g., landslides. For timely and reliable forecasts from such data, we developed a new statistical approach based on two advanced ec...
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Serhii Domoroshchyn,Alexandr Sakhno
Pág. 70 - 81
The approach has been developed to determining the numerical value of a failure probability and to forecasting the resource of an instrument transformer cell at the time of observation. Underlying a given approach is the control over the main parameters ...
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