Analysis and prediction of TBM performance in blocky rock conditions at the Lotschberg Base Tunnel
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FMRI time course processing is traditionally performed using linear regression followed by statistical hypothesis testing. While this analysis method is robust against noise, it relies strongly on the signal model. In this paper, we propose a non-parametri ...
Spie-Int Soc Optical Engineering, Po Box 10, Bellingham, Wa 98227-0010 Usa2007
FMRI time course processing is traditionally performed using linear regression followed by statistical hypothesis testing. While this analysis method is robust against noise, it relies strongly on the signal model. In this paper, we propose a non-parametri ...
The European Union (EU) has adopted directives requiring that Member States take measures to reach a “good” chemical status of water resources by the year 2015 (Water Framework Directive: WFD). In order to achieve the environmental objectives for groundwat ...
Hierarchical penalization is a generic framework for incorporating prior information in the fitting of statistical models, when the explicative variables are organized in a hierarchical structure. The penalizer is a convex functional that performs soft sel ...
Technical difficulties associated with tunnelling operations in tectonized geological settings are frequently encountered. They may include instantaneous and delayed cavity convergence, sudden collapse of walls or roof of a gallery, outpouring of fault-fil ...
Railway ballast consists of crushed aggregate and serves as foundation and drainage for railway tracks. Over time, ballast loses its geotechnical properties and cannot be reused within the rail industry but can be sold on to other users to be utilized as a ...
This work evaluates three techniques of calibrating capacitance (dielectric) spectrometers used for on-line monitoring of biomass: modeling of cell properties using the theoretical Cole-Cole equation, linear regression of dual-frequency capacitance measure ...
Hierarchical penalization is a generic framework for incorporating prior information in the fitting of statistical models, when the explicative variables are organized in a hierarchical structure. The penalizer is a convex functional that performs soft sel ...
A new connectionist model for the solution of piecewise lin- ear regression problems is introduced; it is able to reconstruct both con- tinuous and non continuous real valued mappings starting from a finite set of possibly noisy samples. The approximating ...
A new learning algorithm for solving piecewise linear regression problems is proposed. It is able to train a proper multilayer feedforward neural network so as to reconstruct a target function assuming a different linear behavior on each set of a polyhedra ...