Search results for "Adaptive regression"

Application of selected methods of black box for modelling the settleability process in wastewater treatment plant

2017

The paper described how the results of measurement s of inflow wastewater temperature in the chamber, a degree of external and internal recirculation in the biological-mechanical wastewater treatment plan t (WWTP) in Cedzyna near Kielce, Poland, were used to make predictions of settleability of activated sludge. Three methods,namely: multivariate adaptive regression splines (MARS), random forests (RF) and modified random forests (RF+ SOM) were employed to compute activated sludge settleability. The results of analysis indicate that modified random forests demonstrate the best predictive abilities.

Landform classification: a high-performing mapping unit partitioning tool for landslide susceptibility assessment—a test in the Imera River basin (no…

2022

In landslide susceptibility studies, the type of mapping unit adopted affects the obtained models and maps in terms of accuracy, robustness, spatial resolution and geomorphological adequacy. To evaluate the optimal selection of these units, a test has been carried out in an important catchment of northern Sicily (the Imera River basin), where the spatial relationships between a set of predictors and an inventory of 1608 rotational/translational landslides were analysed using the multivariate adaptive regression splines (MARS) method. In particular, landslide susceptibility models were prepared and compared by adopting four different types of mapping units: the largely adopted grid cells (PX…

ANALISI GIS E MODELLI STATISTICI PER LA VALUTAZIONE DELLA SUSCETTIBILITÀ DA FRANA A SCALA DI BACINO: IL CASO STUDIO DEL BACINO DEL TORRENTE MARVELLO

Lo studio condotto nel presente lavoro di tesi ha affrontato il tema della valutazione, a scala di bacino idrografico, della suscettibilità ai fenomeni di tipo colamento, attraverso l’applicazione di modelli statistici e tecniche di analisi spaziale GIS. La fase iniziale della preparazione di un modello di suscettibilità da frana prevede la realizzazione di un inventario degli eventi verificatesi nell’area di studio. Questo passo è di fondamentale importanza, considerando che proprio attraverso l’archivio frane è possibile analizzare ed individuare le condizioni che in passato hanno favorito l’innesco dei movimenti di versante. L’identificazione di queste condizioni, infatti, consente di pr…

Assessment of Gully Erosion Susceptibility Using Multivariate Adaptive Regression Splines and Accounting for Terrain Connectivity

2017

In this work, we assessed gully erosion susceptibility in two adjacent cultivated catchments of Sicily (Italy) by employing multivariate adaptive regression splines (MARS) and a set of geo-environmental variables. To explore the influence of hydrological connectivity on gully occurrence we measured the changes of performance occurred when adding one by one nine predictors reflecting terrain connectivity to a base model that included contributing area and slope gradient. Receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were used to evaluate models performance. Gully predictive models were trained in both the catchments and submitted to internal (in the ca…

Exploring the effect of absence selection on landslide susceptibility models: A case study in Sicily, Italy

2016

Abstract A statistical approach was employed to model the spatial distribution of rainfall-triggered landslides in two areas in Sicily (Italy) that occurred during the winter of 2004–2005. The investigated areas are located within the Belice River basin and extend for 38.5 and 10.3 km 2 , respectively. A landslide inventory was established for both areas using two Google Earth images taken on October 25th 2004 and on March 18th 2005, to map slope failures activated or reactivated during this interval. Geographic Information Systems (GIS) were used to prepare 5 m grids of the dependent variables (absence/presence of landslide) and independent variables (lithology and 13 DEM-derivatives). Mul…

Mapping Susceptibility to Debris Flows Triggered by Tropical Storms: A Case Study of the San Vicente Volcano Area (El Salvador, CA)

2021

In this study, an inventory of storm-triggered debris flows performed in the area of the San Vicente volcano (El Salvador, CA) was used to calibrate predictive models and prepare a landslide susceptibility map. The storm event struck the area in November 2009 as the result of the simultaneous action of low-pressure system 96E and Hurricane Ida. Multivariate Adaptive Regression Splines (MARS) was employed to model the relationships between a set of environmental variables and the locations of the debris flows. Validation of the models was performed by splitting 100 random samples of event and non-event 10 m pixels into training and test subsets. The validation results revealed an excellent (…

Deep Importance Sampling based on Regression for Model Inversion and Emulation

2021

Understanding systems by forward and inverse modeling is a recurrent topic of research in many domains of science and engineering. In this context, Monte Carlo methods have been widely used as powerful tools for numerical inference and optimization. They require the choice of a suitable proposal density that is crucial for their performance. For this reason, several adaptive importance sampling (AIS) schemes have been proposed in the literature. We here present an AIS framework called Regression-based Adaptive Deep Importance Sampling (RADIS). In RADIS, the key idea is the adaptive construction via regression of a non-parametric proposal density (i.e., an emulator), which mimics the posteri…

Assessment of susceptibility to earth-flow landslide using logistic regression and multivariate adaptive regression splines: A case of the Belice Riv…

2015

Abstract In this paper, terrain susceptibility to earth-flow occurrence was evaluated by using geographic information systems (GIS) and two statistical methods: Logistic regression (LR) and multivariate adaptive regression splines (MARS). LR has been already demonstrated to provide reliable predictions of earth-flow occurrence, whereas MARS, as far as we know, has never been used to generate earth-flow susceptibility models. The experiment was carried out in a basin of western Sicily (Italy), which extends for 51 km 2 and is severely affected by earth-flows. In total, we mapped 1376 earth-flows, covering an area of 4.59 km 2 . To explore the effect of pre-failure topography on earth-flow sp…

Predicting the landslides triggered by the 2009 96E/Ida tropical storms in the Ilopango caldera area (El Salvador, CA): optimizing MARS-based model b…

2019

The main topic of this research was to evaluate the effect in the performance of stochastic landslide susceptibility models, produced by differences between the triggering events of the calibration and validation datasets. In the Caldera Ilopango area (El Salvador), MARS (multivariate adaptive regression splines)-based susceptibility modeling was applied using a set of physical–environmental predictors and two remotely recognized landslide inventories: one dated at 2003 (1503 landslides), which was the result of a normal rainfall season, and one which was produced by the combined effect of the Ida hurricane and the 96E tropical depression in 2009 (2237 landslides). Both the event inventorie…

Predicting sediment deposition rate in check-dams using machine learning techniques and high-resolution DEMs

2021

Sediments accumulated in check dams are a valuable measure to estimate soil erosion rates. Here, geographic information systems (GIS) and three machine learning techniques (MARS-multivariate adaptive regression splines, RF-random forest and SVM-support vector machine) were used, for the first time, to predict sediment deposition rate (SR) in check-dams located in six watersheds in SW Spain. There, 160 dry-stone check dams (~ 77.8 check-dams km−2), accumulated sediments during a period that varied from 11 to 23 years. The SR was estimated in former research using a topographical method and a high-resolution Digital Elevation Model (DEM) (average of 0.14 m3 ha−1 year−1). Nine environmental-to…