Fault detection of the electric vehicle battery system is vital for safe driving, energy economy, and lifetime extension. This paper proposes a data-driven method to achieve early accurate fault realize rapid warning. The first adopts support vector data description model mapping feature unlabeled voltage temperature into minimum volume hypersphere in high-dimensional space. When located outsid...

This paper investigates the application of novelty detection techniques to the problem of drug profiling in forensic science. Numerous one-class classifiers are tried out, from the simple k-means to the more elaborate Support Vector Data Description algorithm. The target application is the classification of illicit drugs samples as part of an existing trafficking network or as a new cluster. A ...

This paper introduces the Graph Embedded One-Class Support Vector Machine and Graph Embedded Support Vector Data Description methods. These methods constitute novel extensions of the One-Class Support Vectors Machines and Support Vector Data Description, incorporating generic graph structures that express geometric data relationships of interest in their optimization process. Local or global re...

Abstract In this paper, a multi-sphere support vector clustering algorithm (SHMSVC) is proposed, which is based on statistical histogram, suitable for large data set, robust to noise and outliers, and able to automatically determine the number of clusters, and identify data points with arbitrary contours of cluster boundaries. The proposed SHMSVC algorithm consists of two major phases. In the f...