Search results for "Mining"
showing 10 items of 1730 documents
Comparing Recurrent Neural Networks using Principal Component Analysis for Electrical Load Predictions
2021
Electrical demand forecasting is essential for power generation capacity planning and integrating environment-friendly energy sources. In addition, load predictions will help in developing demand-side management in coordination with renewable power generation. Meteorological conditions influence urban area load pattern; therefore, it is vital to include weather parameters for load predictions. Machine Learning algorithms can effectively be used for electrical load predictions considering impact of external parameters. This paper explores and compares the basic Recurrent Neural Networks (RNN); Simple Recurrent Neural Networks (Vanilla RNN), Gated Recurrent Units (GRU), and Long Short-Term Me…
The lift computation for an oscillating flat plate in incompressible potential flow
1994
The initial aim of this work was the estimation of the lift acting on a flat plate performing small oscillations in a plane uniform stream by means of a simplified model based on one or at the most two lumped vortices, and the assessment of its results by comparison to those that were exact. The model was found to work well up to a reduced frequency of about 1 or 2, above which the results diverged from those that were correct. In order to improve the model, its behaviour at very high frequencies was then investigated, discovering: (i) that if the number of lumped vortices is greater than one the possibility to impose all boundary conditions is subject to certain geometrical constraints; (i…
Cost-effective Multiresolution schemes for Shock Computations
2009
Harten's Multiresolution framework has provided a fruitful environment for the development of adaptive codes for hyperbolic PDEs. The so-called cost-effective alternative [4,8,21] seeks to achieve savings in the computational cost of the underlying numerical technique, but not in the overall memory requirements of the code. Since the data structure of the basic algorithm does not need to be modified, it provides a set of tools that can be easily implemented into existing codes and that can be very useful in order to speed up the numerical simulations involved in the testing process that is associated to the development of new numerical schemes. In this paper we present two different applica…
An Empirical Evaluation of Common Vector Based Classification Methods and Some Extensions
2008
An empirical evaluation of linear and kernel common vector based approaches has been considered in this work. Both versions are extended by considering directions (attributes) that carry out very little information as if they were null. Experiments on different kinds of data confirm that using this as a regularization parameter leads to usually better (and never worse) results than the basic algorithms.
Forecast of Study Success in the STEM Disciplines Based Solely on Academic Records
2020
We present an approach to the forecast of the study success in selected STEM disciplines (computer science, mathematics, physics, and meteorology), solely based on the academic record of a student so far, without access to demographic or socioeconomic data. The purpose of the analysis is to improve student counseling, which may be essential for finishing a study program in one of the above mentioned fields. Technically, we show the successful use of propositionalization on relational data from educational data mining, based on standard aggregates and basic LSTM-trained aggregates.
On Distinguishing between Reliable and Unreliable Sensors Without a Knowledge of the Ground Truth
2015
In many applications, data from different sensors are aggregated in order to obtain more reliable information about the process that the sensors are monitoring. However, the quality of the aggregated information is intricately dependent on the reliability of the individual sensors. In fact, unreliable sensors will tend to report erroneous values of the ground truth, and thus degrade the quality of the fused information. Finding strategies to identify unreliable sensors can assist in having a counter-effect on their respective detrimental influences on the fusion process, and this has has been a focal concern in the literature. The purpose of this paper is to propose a solution to an extreme…
Data sets for energy rating of photovoltaic modules
2013
Abstract A proposal for generating standard climatic data sets for use in energy rating of photovoltaic (PV) modules is presented which will give a good comparability between different technologies. The current proposal of standard data sets consisting of “typical days” do not give realistic estimates of PV performance and thus is not sufficient as a rating standard. A dataset striking the balance between being significant for any location but does not consisting of too much data is required. A method to generate such a dataset is presented, meeting all the requirements of an international standard while being sufficiently accurate to differentiate between different devices of different man…
A Landslide in Overconsolidated Clays that Has Involved an Important Road of Access to an Internal Mountain Town
2019
The paper presents a case study on the interference of a landslide in overcosolidated clays, triggered in autumn 2004 - winter 2005 by high pore water pressures, on the usability of an important provincial road of an internal town. In the period of 2004–2019 the landslide suffered several mobilisations that led to temporary closures of the road and continuous interventions on the roadway for its use, that caused significant inconvenience for the population and damage to the commercial, sanitary, touristic, agricultural and other activities. In 2018 a study has allowed to identify the kinematic characters of the landslide and the depth of the sliding surface. The study has confirmed that the…
Dataset shift adaptation with active queries
2011
In remote sensing image classification, it is commonly assumed that the distribution of the classes is stable over the entire image. This way, training pixels labeled by photointerpretation are assumed to be representative of the whole image. However, differences in distribution of the classes throughout the image make this assumption weak and a model built on a single area may be suboptimal when applied to the rest of the image. In this paper, we investigate the use of active learning to correct the shifts that may appear when training and test data do not come from the same distribution. Experiments are carried out on a VHR remote sensing classification scenario showing that active learni…
Rockburst induced ground motion—a comparative study
2004
Abstract While rockbursts from underground copper mining in Western Poland normally produce surface peak ground accelerations (PGA) and velocities of 0.05–0.1 g and 1–3 cm/s, occasionally these peak motions may exceed 0.15 g and 10 cm/s, respectively. These larger motions are of considerable concern and an investigation has been undertaken to define the nature of these larger induced ground motions. This paper compares these rockburst motions with low intensity earthquakes. Various strong motion parameters such as PGA, peak ground velocity (PGV) and displacements as well as strong motion duration, Arias intensity, Fourier and response spectra are compared with those from earthquakes. It is …