Search results for "stochastic modelling"
showing 10 items of 86 documents
Chlorophyll Concentration Retrieval by Training Convolutional Neural Network for Stochastic Model of Leaf Optical Properties (SLOP) Inversion
2020
Miniaturized hyperspectral imaging techniques have developed rapidly in recent years and have become widely available for different applications. Combining calibrated hyperspectral imagery with inverse physically based reflectance models is an interesting approach for estimating chlorophyll concentrations that are good indicators of vegetation health. The objective of this study was to develop a novel approach for retrieving chlorophyll a and b values from remotely sensed data by inverting the stochastic model of leaf optical properties using a one-dimensional convolutional neural network. The inversion results and retrieved values are validated in two ways: A classical machine learning val…
Stochastic models for wind speed forecasting
2011
Abstract This paper is concerned with the problem of developing a general class of stochastic models for hourly average wind speed time series. The proposed approach has been applied to the time series recorded during 4 years in two sites of Sicily, a region of Italy, and it has attained valuable results in terms both of modelling and forecasting. Moreover, the 24 h predictions obtained employing only 1-month time series are quite similar to those provided by a feed-forward artificial neural network trained on 2 years data.
On the first- and second-order statistics of the capacity of N*Nakagami-m channels for applications in cooperative networks
2012
This article deals with the derivation and analysis of the statistical properties of the instantaneous channel capacitya of N*Nakagami-m channels, which has been recently introduced as a suitable stochastic model for multihop fading channels. We have derived exact analytical expressions for the probability density function (PDF), cumulative distribution function (CDF), level-crossing rate (LCR), and average duration of fades (ADF) of the instantaneous channel capacity of N*Nakagami-m channels. For large number of hops, we have studied the first-order statistics of the instantaneous channel capacity by assuming that the fading amplitude of the channel can approximately be modeled as a lognor…
ORGANIZED LEARNING MODELS (PURSUER CONTROL OPTIMISATION)
1983
Abstract The concept of Organized Learning is defined, and some random models are presented. For Not Transferable Learning, it is necessary to start from an instantaneous learning; by a discrete way, we must form a stochastic model considering the probability of each path; with a continue aproximation, we can study the evolution of the internal state through to consider the relative and absolute probabilities, by means of differential equations systems. For Transferable Learning, the instantaneous learning give us directly the System evolution. So, the Algoritmes for the different models are compared.
Ambit processes and stochastic partial differential equations
2011
Ambit processes are general stochastic processes based on stochastic integrals with respect to Levy bases. Due to their flexible structure, they have great potential for providing realistic models for various applications such as in turbulence and finance. This papers studies the connection between ambit processes and solutions to stochastic partial differential equations. We investigate this relationship from two angles: from the Walsh theory of martingale measures and from the viewpoint of the Levy noise analysis.
Fluctuation-dissipation relations for Markov processes.
2005
The fluctuation-dissipation relation is calculated for stochastic models obeying a master equation with continuous time. In the general case of a nonstationary process, there appears to be no simple relation between the response and the correlation. Also, if one considers stationary processes, the linear response cannot be expressed via time-derivatives of the correlation function alone. In this case, an additional function, which has rarely been discussed previously, is required. This so-called asymmetry depends on the two times also relevant for the response and the correlation and it vanishes under equilibrium conditions. The asymmetry can be expressed in terms of the propagators and the…
Cost analysis of a vaccination strategy for respiratory syncytial virus (RSV) in a network model
2010
[EN] In this paper an age-structured mathematical model for respiratory syncytial virus (RSV) is proposed where children younger than one year old, who are the most affected by this illness, are specially considered. Real data of hospitalized children in the Spanish region of Valencia are used in order to determine some seasonal parameters of the model. Once the parameters are determined, we propose a complete stochastic network model to study the seasonal evolution of the respiratory syncytial virus (RSV) epidemics. In this model every susceptible individual can acquire the disease after a random encounter with any infected individual in the social network. The edges of a complete graph co…
MDA: a MATLAB-based program for morphospace-disparity analysis
2003
A MATLAB® program that examines patterns of state-space occupation is described. Four subroutines are available with which to visualize morphospace patterns: (i) in terms of their features such as dispersion, aggregation and location, thereby allowing users to extract complementary quantitative information about how the state-space is structured, and (ii) in terms of changes in those patterns that can be compared with other biotic (e.g., extinction, origination rates) or abiotic (e.g., environmental proxy) information. The program incorporates many of the latest and most widely used statistical parameters for describing multivariate spaces. The parameters are estimated on the basis of boots…
Multivariate Gaussian criteria in SMAA
2006
Abstract We consider stochastic multicriteria decision-making problems with multiple decision makers. In such problems, the uncertainty or inaccuracy of the criteria measurements and the partial or missing preference information can be represented through probability distributions. In many real-life problems the uncertainties of criteria measurements may be dependent. However, it is often difficult to quantify these dependencies. Also, most of the existing methods are unable to handle such dependency information. In this paper, we develop a method for handling dependent uncertainties in stochastic multicriteria group decision-making problems. We measure the criteria, their uncertainties and…
A critical view on temperature modelling for application in weather derivatives markets
2012
In this paper we present a stochastic model for daily average temperature. The model contains seasonality, a low-order autoregressive component and a variance describing the heteroskedastic residuals. The model is estimated on daily average temperature records from Stockholm (Sweden). By comparing the proposed model with the popular model of Campbell and Diebold (2005), we point out some important issues to be addressed when modelling the temperature for application in weather derivatives market.