Search results for "vector [form factor]"
showing 10 items of 770 documents
Optimization of Complex SVM Kernels Using a Hybrid Algorithm Based on Wasp Behaviour
2010
The aim of this paper is to present a new method for optimization of SVM multiple kernels The kernel substitution can be used to define many other types of learning machines distinct from SVMs We introduced a new hybrid method which uses in the first level an evolutionary algorithm based on wasp behaviour and on the co-mutation operator LR−Mijn and in the second level a SVM algorithm which computes the quality of chromosomes The most important details of our algorithms are presented The testing and validation proves that multiple kernels obtained using our genetic approach are improving the classification accuracy up to 94.12% for the “leukemia” data set.
Definition and Performance Evaluation of a Robust SVM Based Fall Detection Solution
2012
We propose an automatic approach to detect falls in home environment. A Support Vector Machine based classifier is fed by a set of selected features extracted from human body silhouette tracking. The classifier is followed by filtering operations taking into account the temporal nature of a video. The features are based on height and width of human body bounding box, the user's trajectory with her/his orientation, Projection Histograms and moments of order 0, 1 and 2. We study several combinations of usual transformations of the features (Fourier Transform, Wavelet transform, first and second derivatives), and we show experimentally that it is possible to achieve high performance using a si…
An AI Walk from Pharmacokinetics to Marketing
2009
This work is intended for providing a review of reallife practical applications of Artificial Intelligence (AI) methods. We focus on the use of Machine Learning (ML) methods applied to rather real problems than synthetic problems with standard and controlled environment. In particular, we will describe the following problems in next sections: • Optimization of Erythropoietin (EPO) dosages in anaemic patients undergoing Chronic Renal Failure (CRF). • Optimization of a recommender system for citizen web portal users. • Optimization of a marketing campaign. The choice of these problems is due to their relevance and their heterogeneity. This heterogeneity shows the capabilities and versatility …
Experiments in Value Function Approximation with Sparse Support Vector Regression
2004
We present first experiments using Support Vector Regression as function approximator for an on-line, sarsa-like reinforcement learner. To overcome the batch nature of SVR two ideas are employed. The first is sparse greedy approximation: the data is projected onto the subspace spanned by only a small subset of the original data (in feature space). This subset can be built up in an on-line fashion. Second, we use the sparsified data to solve a reduced quadratic problem, where the number of variables is independent of the total number of training samples seen. The feasability of this approach is demonstrated on two common toy-problems.
Downscaling and improving the wind forecasts from NWP for wind energy applications using support vector regression
2020
Abstract The stochastic nature of wind poses challenges in the large scale integration of wind energy with the grid. Wind characteristics at a site may significantly vary with time. which will be reflected on the wind power production. Understanding and managing such variations could be challenging for wind farm owners. energy traders and grid operators. In this work. we propose models based on support vector regression (SVR) to downscale the speed and direction of wind at a specific site using both historical observed measurements and numerical weather predictions (NWP). Several meteorological variables. considered to have potential influence on the wind. were used in the feature selection…
Real-time flaw detection on complex part: Study of SVM and hyperrectangle based method
2002
We present in this paper the study of two classifications methods used in order to control in real-time some industrials parts. We present the practical frame in which is made the operations, natures of the anomaly to be detected as well as the features extractions method. We tested two techniques of classification, with different algorithm complexities and performances. We compare the results obtained on various features spaces. We end by a combinatorial perspective of results of classification.
CFD Simulation of Particle Distribution in a Multiple-impeller High-Aspect-Ratio Stirred Vessel
2000
Publisher Summary This chapter describes fully predictive simulations of solid–liquid suspensions in a high-aspect-ratio, multiple-impeller stirred tank. These are performed by using the Inner Outer impeller modeling technique coupled with the Multi Fluid Model (MFM) for the treatment of the dispersed phase. The strongly simplified Settling Velocity Model (SVM) is also tested. The effects of free-stream turbulence on the drag coefficient CD and particle settling velocity are accounted for by means of a recently proposed correlation. Comparison of simulation results with experimental particle concentration profiles shows that the MFM approach leads to fair agreement with experimental data. R…
A Review of Kernel Methods in ECG Signal Classification
2011
Kernel methods have been shown to be effective in the analysis of electrocardiogram (ECG) signals. These techniques provide a consistent and well-founded theoretical framework for developing nonlinear algorithms. Kernel methods exhibit useful properties when applied to challenging design scenarios, such as: (1) when dealing with low number of (potentially high dimensional) training samples; (2) in the presence of heterogenous multimodalities; and (3) with different noise sources in the data. These characteristics are particularly appropriate for biomedical signal processing and analysis, and hence, the widespread of these techniques in biomedical signal processing in general, and in ECG dat…
Kernel-based retrieval of atmospheric profiles from IASI data
2011
This paper proposes the use of kernel ridge regression (KRR) to derive surface and atmospheric properties from hyperspectral infrared sounding spectra. We focus on the retrieval of temperature and humidity atmospheric profiles from Infrared Atmospheric Sounding Interferometer (MetOp-IASI) data, and provide confidence maps on the predictions. In addition, we propose a scheme for the identification of anomalies by supervised classification of discrepancies with the ECMWF estimates. For the retrieval, we observed that KRR clearly outperformed linear regression. Looking at the confidence maps, we observed that big discrepancies are mainly due to the presence of clouds and low emissivities in de…
Applications of Kernel Methods
2009
In this chapter, we give a survey of applications of the kernel methods introduced in the previous chapter. We focus on different application domains that are particularly active in both direct application of well-known kernel methods, and in new algorithmic developments suited to a particular problem. In particular, we consider the following application fields: biomedical engineering (comprising both biological signal processing and bioinformatics), communications, signal, speech and image processing.