Search results for "Data mining"

SIGNAL ANALYSIS AND PERFORMANCE EVALUATION OF A VEHICLE CRASH TEST WITH A FIXED SAFETY BARRIER BASED ON HAAR WAVELETS

2011

Author's version of an article published in the journal: International Journal of Wavelets, Multiresolution and Information Processing. Also available from the publisher at: http://dx.doi.org/10.1142/s0219691311003979 This paper deals with the wavelet-based performance analysis of the safety barrier for use in a full-scale test. The test involves a vehicle, a Ford Fiesta, which strikes the safety barrier at a prescribed angle and speed. The vehicle speed before the collision was measured. Vehicle accelerations in three directions at the center of gravity were measured during the collision. The yaw rate was measured with a gyro meter. Using normal speed and high-speed video cameras, the beha…

Adaptive Techniques for Microarray Image Analysis with Related Quality Assessment

2007

We propose novel techniques for microarray image analysis. In particular, we describe an overall pipeline able to solve the most common problems of microarray image analysis. We pro- pose the microarray image rotation algorithm (MIRA) and the statis- tical gridding pipeline (SGRIP) as two advanced modules devoted to restoring the original microarray grid orientation and to detecting, the correct geometrical information about each spot of input mi- croarray, respectively. Both solutions work by making use of statis- tical observations, obtaining adaptive and reliable information about each spot property. They improve the performance of the microarray image segmentation pipeline (MISP) we rec…

Proceedings of MLSP2012 [front matter]

2012

Proba-V cloud detection Round Robin: Validation results and recommendations

2017

This paper discusses results from 12 months of a Round Robin exercise aimed at the inter-comparison of different cloud detection algorithms for Proba-V. Clouds detection is a critical issue for satellite optical remote sensing, since potential errors in cloud masking directly translates into significant uncertainty in the retrieved downstream geophysical products. Cloud detection is particularly challenging for Proba-V due to the presence of a limited number of spectral bands and the lack of thermal infrared bands. The main objective of the project was the inter-comparison of several cloud detection algorithms for Proba-V over a wide range of surface types and environmental conditions. Prob…

New Similarity Rules for Mining Data

2006

Variability and noise in data-sets entries make hard the discover of important regularities among association rules in mining problems. The need exists for defining flexible and robust similarity measures between association rules. This paper introduces a new class of similarity functions, SF's, that can be used to discover properties in the feature space X and to perform their grouping with standard clustering techniques. Properties of the proposed SF's are investigated and experiments on simulated data-sets are also shown to evaluate the grouping performance.

An efficient prototype merging strategy for the condensed 1-NN rule through class-conditional hierarchical clustering

2002

Abstract A generalized prototype-based classification scheme founded on hierarchical clustering is proposed. The basic idea is to obtain a condensed 1-NN classification rule by merging the two same-class nearest clusters, provided that the set of cluster representatives correctly classifies all the original points. Apart from the quality of the obtained sets and its flexibility which comes from the fact that different intercluster measures and criteria can be used, the proposed scheme includes a very efficient four-stage procedure which conveniently exploits geometric cluster properties to decide about each possible merge. Empirical results demonstrate the merits of the proposed algorithm t…

Performance evaluation of fuzzy-neural HTTP request distribution for Web clusters

2006

In this paper we present the performance evaluation of our fuzzy-neural HTTP request distribution algorithm called FNRD, which assigns each incoming request to the server in the Web cluster with the quickest expected response time. The fuzzy mechanism is used to estimate the expected response times. A neural-based feedback loop is used for real-time tuning of response time estimates. To evaluate the system, we have developed a detailed simulation and workload model using CSIM19 package. Our simulations show that FNRD can be more effective than its competitors.

Soft computing-based aggregation methods for human resource management

2008

Abstract We are interested in the personnel selection problem. We have developed a flexible decision support system to help managers in their decision-making functions. This DSS simulates experts’ evaluations using ordered weighted average (OWA) aggregation operators, which assign different weights to different selection criteria. Moreover, we show an aggregation model based on efficiency analysis to put the candidates into an order.

Applying Cathegorical Metrics on Fuzzy Systems

2007

This work analyzes the categorical metrics usage on a very specific subset of Intelligent Systems: Fuzzy Systems. Several characteristics for such systems must be carefully evaluated when metrics and indicators are defined, in order to consider the fuzzy essence as part of the evaluation result. A set of metrics and indicators are defined and applied to the classical inverted pendulum problem. The paper does not intend to provide an exhaustive analysis of the quality evaluation on soft computing problem. It just presents a way to start the study of quality measure in that area.

Soft Computing Methods for Personnel Selection Based on the Valuation of Competences

2014

Personnel selection based on candidates' competences is a difficult task due to the imprecise description of the applicants' competences and to the existence of several experts simultaneously evaluating those attributes. In this context, fuzzy sets theory provides suitable tools for the attainment of the maximum possible information from imprecise data. In this work, personnel selection methods are proposed that rely on the definition of an ideal candidate. Aggregated fuzzy valuations of each candidate are obtained taking into account the individual valuations provided by the experts. Then, candidates are ranked based on their similarity with the ideal candidate. Three different scenarios a…