The inconsistent characteristics of individual power batteries in a battery pack can seriously affect the performance and service life of the whole pack. Battery grouping is an effective approach for dealing with the inconsistency problem by grouping batteries with similar characteristics in the same battery pack. In actual production, the battery grouping process still relies on the traditiona...

This paper deals with the association step in a multi-sensor multitarget tracking process. A new parameterless credal method for track-to-track assignment is proposed and compared with parameter-dependent methods, namely: the well known Global Nearest Neighbor algorithm (GNN) and a credal method recently proposed by Denœux et al.

A genetic algorithm is applied for selecting a reference set for the k-Nearest Neighbors rule. The performance has been evaluated on a medical data set by the rotation method. The results are commented together with those obtained with the standard k-NN, random selection, Wilson's technique, and the MULTIEDIT algorithm.

The nearest neighbor classification is a simple and effective technique for pattern recognition. The performance of this technique is known to be sensitive to the distance function used in classifying a test instance. In this paper, we propose a technique to learn sample weights via maximizing classification consistency. Experimental analysis shows that the distance trained in this way enlarges...

In this paper we combining statistical, structural Global transformation and moments features to form hybrid feature vector .We are combining Classifiers for achieving high accuracy for Devanagari Script. To abolish the hitch of misclassification and increase the classifier accurac combining SVM and KNN together. The dataset used for experiment are created by us.

Text information processing depends critically on the proper representation of documents. Traditional models, like the vector space model, have significant limitations because they do not consider semantic relations amongst terms. In this paper we analyze a document representation using the association graph scheme and present a new approach called Global Association Distance Model (GADM). At t...

Given a set of clients C , a set of facilities F and a query q ∈ F , a reverse k-nearest neighbor (RkNN) query retrieves every client c ∈ C for which q is one of the k closest facilities. In the past few years, RkNN queries have received significant research attention due to their wide range of applications. In this paper, we study the problem of continuous monitoring of RkNN queries in road ne...

A new classiier using neighborhood information in the framework of the Dempster-Shafer theory of evidence has recently been introduced. This approach consists in considering each neighbor of a pattern to be classiied as an item of evidence supporting certain hypotheses concerning the class membership of that pattern. In this paper, an adap-tive version of this method is proposed, in which the p...

This paper introduces a straightforward generalization of the well-known LVQ1 algorithm for nearest neighbour classifiers that includes the standard LVQ1 and the k-means algorithms as special cases. It is based on a regularizing parameter that monotonically decreases the upper bound of the training classification error towards a minimum. Experiments using 10 real data sets show the utility of t...