This paper demonstrates the feasibility and potential of applying empirical mode decomposition (EMD) to forecast the arrival time behaviors in a parallel batch system. An analysis...
We extend our previous works of deriving linguistic summaries of time series using a fuzzy logic approach to linguistic summarization. We proceed towards a multicriteria analysis o...
This paper presents a wavelet neural-network for learning and approximation of chaotic time series. Wavelet-networks are inspired by both feed-forward neural networks and the theo...
Motivated by a broad range of potential applications, we address the quantile prediction problem of real-valued time series. We present a sequential quantile forecasting model bas...
Negative bias temperature instability (NBTI) has become the dominant reliability concern for nanoscale PMOS transistors. In this paper, a predictive model is developed for the deg...