Search results for "Regression"
showing 10 items of 2619 documents
Fusing optical and SAR time series for LAI gap filling with multioutput Gaussian processes
2019
The availability of satellite optical information is often hampered by the natural presence of clouds, which can be problematic for many applications. Persistent clouds over agricultural fields can mask key stages of crop growth, leading to unreliable yield predictions. Synthetic Aperture Radar (SAR) provides all-weather imagery which can potentially overcome this limitation, but given its high and distinct sensitivity to different surface properties, the fusion of SAR and optical data still remains an open challenge. In this work, we propose the use of Multi-Output Gaussian Process (MOGP) regression, a machine learning technique that learns automatically the statistical relationships among…
The principal as a key actor in promoting teachers’ innovativeness – analyzing the innovativeness of teaching staff with variance-based partial least…
2018
The study examines the correlation between collective innovativeness of the teaching staff and the principal’s leadership style as well as additional school structure characteristics. The construct...
Análisis de métodos de validación cruzada para la obtención robusta de parámetros biofísicos
2015
[EN] Non-parametric regression methods are powerful statistical methods to retrieve biophysical parameters from remote sensing measurements. However, their performance can be affected by what has been presented during the training phase. To ensure robust retrievals, various cross-validation sub-sampling methods are often used, which allow to evaluate the model with subsets of the field dataset. Here, two types of cross-validation techniques were analyzed in the development of non-parametric regression models: hold-out and k-fold. Selected non-parametric linear regression methods were least squares Linear Regression (LR) and Partial Least Squares Regression (PLSR), and nonlinear methods were…
Analysis of the Russian and World Marker of Telemedicine and Biochipping: Features and Development Prospects
2019
The paper considers the telemedicine and biochipping market and studies the peculiarities of its development and problems in different countries. The purpose is to study the experience of telemedicine and biochipping in the world, and its features and prospects of development. The authors used methods of generalization, comparison, sampling, regression analysis, scientific articles and expert opinions to make a comparative analysis of the experience and results of the implementation of biochipping and telemedicine. The following conclusion was made: with the introduction of biochipping, the problem of a large number of long-term hospital and false ambulance calls will be solved, and the bod…
The influence of climate change on the soil organic carbon content in Italy from 1961 to 2008
2011
Abstract Soils are the biggest carbon store in the world (1500 Gt, e.g. 1.5 × 10 21 g). The European Commission indicates the accounting of soil organic carbon (SOC) variations in space and time as the first step in the strategy for soil protection. It is indeed necessary in evaluating the risk of soil organic matter decline and soil biodiversity decline, and when evaluating the role played by soils in global CO 2 accounting. Previous maps of SOC variations in Italy did not consider the direct effect of climate. There is a marked inter-dependence between SOC and climate. SOC increases with the increase in precipitations and decreases with a rise in temperatures. It is also known that land …
Mesures de la température et spatialisation de l’Ilot de Chaleur Urbain à Dijon
2015
The Territorial Climate Energy Plan (PCET) of the agglomeration of Dijon (Grand Dijon) includes ameasurement campaign (6 June to 28 September 2014). 50 Hobo proV2 thermometers were deployed. The selection of siteswas carried out so that the different types of urban environment (Oke, 2006) are documented. The Urban Heat Island (UHI)is discernible mainly at night, when radiative conditions are well established the day before. It is estimated to 1°C onaverage for the summer, 3-4°C during nights of fine weather. It reached 6°C during the warmest periods of the 2014 summer.A cool axis through the agglomeration shows that vegetation and water can sensibly mitigate the ICU effect.
Assessing the territorial influence of an Iberian worship site. The chemical characterisation of the terracotta from the Iron Age sanctuary of La Ser…
2017
This paper presents the study of the prestigious terracotta votive figurines from the Iberian Iron Age sanctuary of La Serreta (Alicante province, Spain) composed of 174 items. Portable X-ray fluorescence (PXRF) was used to identify elemental markers that permit us to observe the differences between local and non-local terracotta figurines and furthermore to evaluate the geographical influence of the La Serreta sanctuary using Principal Component Analysis (PCA). The Partial Least Squares Discriminant Analysis (PLSDA) statistical method was also used to classify the figurines of uncertain geographical origin. The resulting groups were related to typological and stylistic groups of figurines …
On the role of non-effective code in linear genetic programming
2019
In linear variants of Genetic Programming (GP) like linear genetic programming (LGP), structural introns can emerge, which are nodes that are not connected to the final output and do not contribute to the output of a program. There are claims that such non-effective code is beneficial for search, as it can store relevant and important evolved information that can be reactivated in later search phases. Furthermore, introns can increase diversity, which leads to higher GP performance. This paper studies the role of non-effective code by comparing the performance of LGP variants that deal differently with non-effective code for standard symbolic regression problems. As we find no decrease in p…
Comparative study of modelling the thermal efficiency of a novel straight through evacuated tube collector with MLR, SVR, BP and RBF methods
2021
Abstract Data-based methods are useful for accurate modelling of solar thermal systems. In this work, several artificial neural network (ANN) techniques are proposed to predict the thermal performance of an all-glass straight through evacuated tube solar collector. These are compared to support vector regression analysis. Extensive experimental data sets were collected for training the ANN models. Solar radiation intensity, ambient temperature, wind speed, mass flow rate and collector inlet temperature were selected as the input layer to predict the thermal efficiency of the solar collector. The prediction precision of the ANN models was compared to the multiple linear regression and suppor…
Joint associations of accelerometer-measured physical activity and sedentary time with all-cause mortality: a harmonised meta-analysis in more than 4…
2020
Funder: National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care East Midlands