Robust control chart for nonlinear conditionally heteroscedastic time series based on Huber support vector regression.

This study proposes a control chart that monitors conditionally heteroscedastic time series by integrating the Huber support vector regression (HSVR) and the one-class classification (OCC) method. For this task, we consider the model that incorporates nonlinearity to the generalized autoregressive conditionally heteroscedastic (GARCH) time series, named HSVR-GARCH, to robustly estimate the conditional volatility when the structure of time series is not specified with parameters. Using the squared residuals, we construct the OCC-based control chart that does not require any posterior modifications of residuals unlike previous studies.

Monitoring Volatility Change for Time Series Based on Support Vector Regression.

This paper considers monitoring an anomaly from sequentially observed time series with heteroscedastic conditional volatilities based on the cumulative sum (CUSUM) method combined with support vector regression (SVR). The proposed online monitoring process is designed to detect a significant change in volatility of financial time series. The tuning parameters are optimally chosen using particle swarm optimization (PSO).

Hybrid CUSUM Change Point Test for Time Series with Time-Varying Volatilities Based on Support Vector Regression.

This study considers the problem of detecting a change in the conditional variance of time series with time-varying volatilities based on the cumulative sum (CUSUM) of squares test using the residuals from support vector regression (SVR)-generalized autoregressive conditional heteroscedastic (GARCH) models. To compute the residuals, we first fit SVR-GARCH models with different tuning parameters utilizing a time series of training set. We then obtain the best SVR-GARCH model with the optimal tuning parameters via a time series of the validation set.

Characterization of sulfonated poly(ether ether ketone)/silane nanocomposite membrane for high temperature polymer electrolyte membrane fuel cells.

The perfluorosulfonic acid polymer membrane is most widely used in PEMFCs. However, its some major drawbacks like high cost and performance limitation at high temperature are obstacles of its commercialization. The goal of this study was to develop low cost membranes which have good conductivity in the range of PEMFCs operating temperature.

Poly(dimethyl siloxane) membrane for high temperature proton exchange membrane fuel cells.

Sulfonic acid-based membrane gives the relatively high conductivity only in the presence of water, but phosphoric acid presents the relatively high proton conductivity without water because of its self dissociation natures to develop high temperature PEMFCs. We synthesized the thermostable material that has phosphorous groups based on poly(dimethyl siloxane) (PDMS). PDMS, which is intrinsically hydrophobic was modified to be amphiphilic by substituting end groups with hydrophilic phosphorous groups.