Search results for "PREDICTION"
showing 10 items of 511 documents
Evaluating the effects of forest tree species on rill detachment capacity in a semi-arid environment
2021
Abstract The beneficial effects of plant roots in decreasing soil detachment in forest ecosystems exposed to rill erosion are well known. However, these effects vary largely between different plant species. There has been lots of research into the relationship between root-soil systems and rill erodibility with a particular focus on grass species. Conversely, fewer studies are available for tree species, especially in forests of semi-arid or arid environments. Greater knowledge is therefore needed to identify the most effective tree species against rill erosion in these ecosystems, where water availability is the limiting factor for vegetation growth and afforestation is often the only solu…
Measuring Field Rill Erodibility by a Simplified Method
2015
Many process-oriented erosion prediction models reproduce rill erosion as affected by site-specific parameters, as for example, rill erodibility, and thus, their practical application requires the measurement of these parameters or their estimate. The aim of this paper was establishing a method for indirectly measuring field rill erodibility. A simple mathematical approach based on a known soil detachment equation and accounting for the rill erosion dynamic process is applied. Field measurements carried out for seven natural rainfall events occurring at the plots of the Sparacia experimental station, southern Italy, are used for indirectly measuring the rill erodibility of the investigated …
The Application of Different Model of Multi-Layer Perceptrons in the Estimation of Wind Speed
2012
Wind speed forecasting is essential for effective planning of wind energy exploitation projects. The ability to predict short-term wind speed is a prerequisite for all the operators of the wind energy sector. Consequently it is essential to identify an efficient method for forecasts. In this paper, the wind speed in the province of Trapani (Sicily) is modeled by artificial neural network. Several model of neural network were generated and compared through error measures. Simulation results show that the estimated values of wind speed are in good agreement with the values measured by anemometers..
Non-parametric probabilistic forecasting of academic performance in Spanish high school using an epidemiological modelling approach
2013
Academic underachievement is a concern of paramount importance in Europe, and particularly in Spain, where around of 30% of the students in the last two courses in high school do not achieve the minimum knowledge academic requirement. In order to analyse this problem, we propose a mathematical model via a system of ordinary differential equations to study the dynamics of the academic performance in Spain. Our approach is based on the idea that both, good and bad study habits, are a mixture of personal decisions and influence of classmates. Moreover, in order to consider the uncertainty in the estimation of model parameters, a bootstrapping approach is employed. This technique permits to for…
Early prediction of reading trajectories of children with and without reading instruction in kindergarten : a comparison study of Estonia and Finland
2019
Background: The present study examined differences in the prediction of reading development and reading difficulties in Estonia (n = 348) and Finland (n = 344). These neighbouring countries share many similarities in terms of their language, orthography and educational system; however, they differ in the timing of the onset of reading instruction, which is kindergarten in Estonia and Grade 1 in Finland. Methods: Children's skills were assessed three times – fall and spring in Grade 1 and spring in Grade 2. Results: The results showed that school‐entry rapid automatised naming and reading fluency predicted the development of fluency in Grade 2, but reading fluency was a stronger predictor in…
Genre-adaptive Semantic Computing and Audio-based Modelling for Music Mood Annotation
2016
This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling are proposed. A technique called the ACTwg employs genre-adaptive semantic computing of mood-related social tags, whereas ACTwg-SLPwg combines semantic computing and audio-based modelling, both in a genre-adaptive manner. The proposed techniques are experimentally evaluated at predicting listener ratings related to a set of 600 popular music tracks spanning multiple genres. The results show that ACTwg outpe…
Evaluating the impact of friends in predicting user’s availability in online social networks
2017
In recent years, Online Social Networks (OSNs) have changed the way people connect and interact with each other. Indeed, most people have registered an account on some popular OSNs (such as Facebook, or Google+) which is used to access the system at different times of the days, depending on their life and habits. In this context, understanding how users connect to the OSNs is of paramount importance for both the protection of their privacy and the OSN’s provider (or third-party applications) that want to exploit this information. In this paper, we study the task of predicting the availability status (online/offline) of the OSNs’ users by exploiting the availability information of their frie…
Wear modelling in mild steel orthogonal cutting when using uncoated carbide tools
2007
Abstract Wear prediction in machining has been recently studied by FEM although the use of numerical methods for such applications is still a very challenging research issue. In fact, wear phenomenon involves many aspects related to process mechanics which require a very accurate modelling. In other words, only a very punctual code set-up can help the researchers in order to obtain consistent results in FE analysis. The high relative velocity between chip and tool requires effective material models as well as friction modelling at the interface. Moreover the prediction of temperature distribution is another critical task; in the paper some different procedures are discussed. Subsequently a …
Finding optimal finite biological sequences over finite alphabets: the OptiFin toolbox
2017
International audience; In this paper, we present a toolbox for a specific optimization problem that frequently arises in bioinformatics or genomics. In this specific optimisation problem, the state space is a set of words of specified length over a finite alphabet. To each word is associated a score. The overall objective is to find the words which have the lowest possible score. This type of general optimization problem is encountered in e.g 3D conformation optimisation for protein structure prediction, or largest core genes subset discovery based on best supported phylogenetic tree for a set of species. In order to solve this problem, we propose a toolbox that can be easily launched usin…
A probabilistic estimation and prediction technique for dynamic continuous social science models: The evolution of the attitude of the Basque Country…
2015
In this paper, a computational technique to deal with uncertainty in dynamic continuous models in Social Sciences is presented.Considering data from surveys,the method consists of determining the probability distribution of the survey output and this allows to sample data and fit the model to the sampled data using a goodness-of-fit criterion based the χ2-test. Taking the fitted parameters that were not rejected by the χ2-test, substituting them into the model and computing their outputs, 95% confidence intervals in each time instant capturing the uncertainty of the survey data (probabilistic estimation) is built. Using the same set of obtained model parameters, a prediction over …