As a highly complex multi-input and multi-output system, blast furnace plays an important
role in industrial development. Although much research has been done in the past few …

Abstract Model selection is an important problem of costsensitive SVM (CS-SVM). Although
using solution path to find global optimal parameters is a powerful method for model …

Cross-validation (CV) is a widely adopted approach for selecting the optimal model.
However, the computation of empirical cross-validation error (CVE) has high complexity due …

Negative emotional responses are a growing problem among drivers, particularly in
countries with heavy traffic, and may lead to serious accidents on the road. Measuring stress …

Cloud computing has grown into a critical technology by enabling ground-breaking
capabilities for Internet-dependent computer platforms and software applications. As cloud …

By using signal processing and statistical analysis methods simultaneously, many
heterogeneous features can be produced to describe the bearings fault with more …

Abstract Models with multivariate outputs are widely used for risk assessment and decision-
making in practical applications. In this paper, multi-output support vector regression (M …

Dam failure constitutes a grave threat to human life. However, there is still a lack of
systematic and comprehensive research on the loss of life (L) caused by dam break in …

Machine learning models (Support Vector Regression) were applied for predictions of
several targets for 18-electron half-Heusler phases: a lattice parameter, a bulk modulus, a …

A novel data-driven framework to monitor the health status of high-speed rail suspension
system by measuring train vibrations is proposed herein. Unlike existing methods, this …