We propose a novel method using Locality-Sensitive Hashing (LSH) for solving the optimization problem that arises in training stage of support vector machines large data sets, possibly high dimensions. LSH was introduced as an efficient way to look neighbors dimensional spaces. Random projections-based functions create bins so when great probability points belonging same bin are close, far will...

This study aims to couple the support vector machine (SVM) model with a hydrometeorological wireless sensor network simulate different types of flood events in montane basin. The was tested mid-latitude basin Vydra Šumava Mountains, Central Europe, featuring complex physiography, high dynamics processes, and occurrence floods. is equipped operating headwaters along conventional long-term monito...

Abstract To improve the efficiency of traditional face recognition techniques, this paper proposes a novel algorithm called Image Gradient Feature Compensation (IGFC). Based on gradients along four directions in an image, fusion and compensation method are implemented to obtain features original image. In study, gradient magnitude maps image calculated directions. Fusion differential produced b...

In the present work, use of support vector machine (SVM) algorithm is proposed to generate models that allow predicting geometrical accuracy molds manufactured via single point incremental forming (SPIF) using aluminized steel sheets DX51D AS120 B CO. For this purpose, 27 were manufactured, dummy technique, and employing different process parameters (tool diameter, spindle speed, feed rate, ste...

Deep learning has become a research hotspot in the field of network intrusion detection. In order to further improve detection accuracy and performance, we proposed an model based on improved deep belief (DBN). Traditional neural training methods, like Back Propagation (BP), start train with preset parameters such as randomly initialized weights thresholds, which may bring some issues, e.g., at...

In 2010, Bollen used Twitter data to find high predictability of Twitter sentiment on the stock market. [1]. We hypothesized that while Bollen’s results from analyzing the full breadth of the Twitter pipeline found significant results, fine-tuning the Twitter pipeline to only ‘high-impact’ financial tweets would improve the data signal and further improve results. As a result, we filtered a dat...

A combination forecasting model based on Support Vector Machine (SVM) whose objective is to minimize the structure risk is proposed. The storage failure of two-state materials tends to fail immediately without any recognizable defeats prior to the failure, which increases the difficulty of forecasting, so the combination forecasting model is often used to optimize the prediction effect. The cor...

Résumé. Nous présentons un nouvel algorithme incrémental et parallèle de Séparateur à Vaste Marge (SVM ou Support Vector Machine) pour la classification de très grands ensembles de données en utilisant le processeur de la carte graphique (GPUs, Graphics Processing Units). Les SVMs et les méthodes de noyaux permettent de construire des modèles avec une bonne précision mais ils nécessitent habitu...

Regularized least-squares approaches have been successfully applied to linear system identification. Recent approaches use quadratic penalty terms on the unknown impulse response defined by stable spline kernels, which control model space complexity by leveraging regularity and bounded-input bounded-output stability. This paper extends linear system identification to a wide class of nonsmooth s...