相关论文: A new probabilistic shift away from seismic hazard…
We examine the applicability of modern neural network architectures to the midterm prediction of earthquakes. Our data-based classification model aims to predict if an earthquake with the magnitude above a threshold takes place at a given…
We propose a novel method for analyzing precursory seismic data before an earthquake that treats them as a Markov process and distinguishes the background noise from real fluctuations due to an earthquake. A short time (on the order of…
In health econometric studies we are often interested in quantifying aspects related to the accessibility to medical infrastructures. The increasing availability of data automatically collected through unconventional sources (such as…
In the territory of the Campania region (southern Italy), critical rainfall events periodically trigger dangerous fast slope movements involving ashy and pyroclastic soils originated by the explosive phases of the Mt. Somma-Vesuvius volcano…
Stage IV cosmological surveys will map the universe with unprecedented precision, reducing statistical uncertainties to levels where unmodelled systematics can significantly bias inference. In particular, photometric redshift (photo-z)…
A flood of reliable seismic data will soon arrive. The migration to larger telescopes on the ground may free up 4-m class instruments for multi-site campaigns, and several forthcoming satellite missions promise to yield nearly uninterrupted…
This article considers stochastic algorithms for efficiently solving a class of large scale non-linear least squares (NLS) problems which frequently arise in applications. We propose eight variants of a practical randomized algorithm where…
Recent studies in the literature have introduced a new approach to earthquake forecasting based on representing the space-time patterns of localized seismicity by a time-dependent system state vector in a real-valued Hilbert space and…
Geostatistical seismic inversion is commonly used to infer the spatial distribution of the subsurface petro-elastic properties by perturbing the model parameter space through iterative stochastic sequential simulations/co-simulations. The…
We propose a novel model selection algorithm based on a penalized maximum likelihood estimator (PMLE) for functional hidden dynamic geostatistical models (f-HDGM). These models employ a classic mixed-effect regression structure with…
Fault-slip rockbursts, triggered by seismic rupture of nearby or remote faults, constitute a significant geohazard during deep underground excavations. Although these events occur frequently in underground projects, their underlying…
These are the proceedings of the Second Workshop on GRAPH Inspection and Traversal Engineering (GRAPHITE 2013), which took place on March 24, 2013 in Rome, Italy, as a satellite event of the 16th European Joint Conferences on Theory and…
This work presents a new parametrisation suitable for parameter-space studies of heliocentric Earth-impacting orbits. Originally motivated by the issue of potentially hazardous asteroids (PHAs) and the mitigation of such a risk, we show…
The paper presents a comparison between the results of the analytical assessments of the damage potential of seismic ground motions, based on two different parameters: the Park-Ang damage index and the Sandi instrumental seismic intensity.…
Machine learning models for geotechnical hazard prediction can achieve high accuracy while learning physically inconsistent relationships from sparse or biased training data. Current remedies (post-hoc explainability, such as SHAP and LIME,…
Predicting earthquakes is of the utmost importance, especially to those countries of high risk, and although much effort has been made, it has yet to be realised. Nevertheless, there is a paucity of statistical approaches in seismic studies…
Earthquakes are commonly estimated using physical seismic stations, however, due to the installation requirements and costs of these stations, global coverage quickly becomes impractical. An efficient and lower-cost alternative is to…
Landslides are a recurring, widespread hazard. Preparation and mitigation efforts can be aided by a high-quality, large-scale dataset that covers global at-risk areas. Such a dataset currently does not exist and is impossible to construct…
Timely and accurate assessments of building damage are crucial for effective response and recovery in the aftermath of earthquakes. Conventional preliminary damage assessments (PDA) often rely on manual door-to-door inspections, which are…
In Geosciences a class of phenomena that is widely studied given its real impact on human life are the tectonic faults slip. These landslides have different ways to manifest, ranging from aseismic events of slow displacement (slow slips) to…