Forecasting the number of warranty claims is vitally important formanufacturers/warranty providers in preparing fiscal plans. In existingliterature, a number of techniques such as log-linear Poisson models, Kalmanfilter, time series models, and artificial neural network models have...

Data sets from car insurance companies often have a high-dimensional complex dependency structure. The use of classical statistical methods such as generalized linear models or Tweedie?s compound Poisson model can yield problems in this case. Christmann (2004) proposed a general approach to...

We introduce a multistep-ahead forecasting methodology that combines empirical mode decomposition (EMD) and support vector regression (SVR). This methodology is based on the idea that the forecasting task is simplified by using as input for SVR the time series decomposed with EMD. The outcomes...

Diabetes has become an important public health issue in the twenty-first century, and dialysis treatment has become a large burden on the National Health Insurance of Taiwan. Diabetic nephropathy(DN) is the leading factor that determines whether patients with diabetes will require dialysis....

The volatility of real estate prices is one of the key factors to the decision making of financial institutions, as well as to a country¡¯s economic development. Therefore how to catch the trend of this real estate price has been an important issue for Governments and financial institutions....

Data sets from car insurance companies often have a high-dimensional complex dependency structure. The use of classical statistical methods such as generalized linear models or Tweedie?s compound Poisson model can yield problems in this case. Christmann (2004) proposed a general approach to...

Electric load forecasting is an important issue for a power utility, associated with the management of daily operations such as energy transfer scheduling, unit commitment, and load dispatch. Inspired by strong non-linear learning capability of support vector regression (SVR), this paper...

Control charts have been widely recognised as important tools in system monitoring of abnormal behaviour and quality improvement. Traditional control charts have a major assumption that successive observations are uncorrelated and normally distributed. When this assumption is violated, the...

Electric vehicles (EVs) and the related infrastructure are being developed rapidly. In order to evaluate the impact of factors on the aggregated EV load and to coordinate charging, a model is established to capture the relationship between the charging load and important factors based on data...