Search results for " spline"
showing 10 items of 78 documents
Prediction of BOD5 content of the inflow to the treatment plant using different methods of black box - the case study
2020
The publication presents the possibility of modeling in a 1 d advance of the content of organic compounds in the influent wastewater to the treatment plant, where the content of these compounds is determined by both the biochemical and chemical oxygen demand. To predict the quality of the wastewater at the inflow a set of indicators where used to make measurements on a daily basis. In order to develop statistical models 3 methods where used, namely: multivariate adaptive regression splines (MARS), boosted trees (BT), and genetic programming (GP). The carried-out calculations showed that, to calculate the BOD5 there can only be used models developed on the basis of the value of daily wastewa…
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…
On mathematical modelling of the solid-liquid mixtures transport in porous axial-symmetrical container with Henry and Langmuir sorption kinetics
2018
In this paper we study diffusion and convection filtration problem of one substance through the pores of a porous material which may absorb and immobilize some of the diffusing substances. As an example we consider round cylinder with filtration process in the axial direction. The cylinder is filled with sorbent i.e. absorbent material that passed through dirty water or liquid solutions. We can derive the system of two partial differential equations (PDEs), one expressing the rate of change of concentration of water in the pores of the sorbent and the other - the rate of change of concentration in the sorbent or kinetical equation for absorption. The approximation of corresponding initial b…
ECONOMIC ACTIVITY, CREDIT MARKET CONDITIONS, AND THE HOUSING MARKET
2017
In this paper, we assess the characteristics of the housing market and its main determinants. Using data for 20 industrial countries over the period 1970Q1–2012Q2 and a discrete-time Weibull duration model, we find that the likelihood of the end of a housing boom or a housing bust increases over time. Additionally, we show that the different phases of the housing market cycle are strongly dependent on the economic activity, but credit market conditions are particularly important in the case of housing booms. The empirical findings also indicate that although housing booms have similar lengths in European and non-European countries, housing busts are typically shorter in European countries. …
A spline-based non-linear diffeomorphism for multimodal prostate registration.
2012
This paper presents a novel method for non-rigid registration of transrectal ultrasound and magnetic resonance prostate images based on a non-linear regularized framework of point correspondences obtained from a statistical measure of shape-contexts. The segmented prostate shapes are represented by shape-contexts and the Bhattacharyya distance between the shape representations is used to find the point correspondences between the 2D fixed and moving images. The registration method involves parametric estimation of the non-linear diffeomorphism between the multimodal images and has its basis in solving a set of non-linear equations of thin-plate splines. The solution is obtained as the least…
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…
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 (…
Prediction of debris-avalanches and -flows triggered by a tropical storm by using a stochastic approach: An application to the events occurred in Moc…
2019
Abstract Landslides are among the most dangerous natural processes. Debris avalanches and debris flows in particular have often caused casualties and severe damage to infrastructures in a wide range of environments. The assessment of susceptibility to these phenomena may help policy makers in mitigating the associated risk and thus it has attracted special attention in the last decades. In this experiment, we assessed susceptibility to debris-avalanche and -flow landslides by using a stochastic approach. Two different modeling techniques were employed: i) Multivariate Adaptive Regression Splines (MARS) and ii) Logistic Regression (LR). Both MARS and LR allow for calculating the probability …
Evaluation of debris flow susceptibility in El Salvador (CA): a comparison between Multivariate Adaptive Regression Splines (MARS) and Binary Logisti…
2018
In the studies of landslide susceptibility assessment, which have been developed in recent years, statistical methods have increasingly been applied. Among all, the BLR (Binary Logistic Regression) certainly finds a more extensive application while MARS (Multivariate Adaptive Regression Splines), despite the good performance and the innovation of the strategies of analysis, only recently began to be employed as a statistical tool for predicting landslide occurrence. The purpose of this research was to evaluate the predictive performance and identify possible drawbacks of the two statistical techniques mentioned above, focusing in particular on the prediction of debris flows. To this aim, an…