In the case of U.S. national accounts, the data are revised for the first few years and every decade, which implies that we do not really have the final data. In this paper, we aim to predict the final data, using the preliminary data and/or the revised data. The following predictors are introduced and derived from a context of the nonlinear filtering or smoothing problem, which are: (i) predic...

In this paper, the normalized prediction error of the electroencephalogram (EEG) signal recorded at five different mental tasks was computed. The results indicate that there exists predictability in the EEG signal beyond the baseline prediction of the mean and the one-stepahead normalized prediction error of EEG signal vary greatly when different mental tasks are implemented, which implies that...

the prediction of the joint angle position, especially during tremor bursts, can be useful for detecting, tracking, and forecasting tremors. thus, this research proposes a new model for predicting the wrist joint position during rhythmic bursts and inter‑burst intervals. since a tremor is an approximately rhythmic and roughly sinusoidal movement, neural oscillators have been selected to underli...

the wepp physically model is able to dynamically simulate runoff and soil erosion using physical concepts of erosion and hydraulic of overland flow science considering plant growth, residue decomposition, winter process. determination of the capability of this model in runoff and erosion estimation in different range type with investigation the effects of management were the main objectives of ...

Introduction: In radiotherapy with external surrogates, exact information of tumor position is one of the key factors that improves treatment delivery. Many dynamic tumors in thorax region of patient move mainly due to respiration and are known as intra-fractional motion error that must be compensated, as well. One of clinical strategy is using Stereotactic Body Radiation Thera...

The notion of generalization ability can be defined precisely as the prediction risk, the expected performance of an estimator in predicting new observations. In this paper, we propose the prediction risk as a measure of the generalization ability of multi-layer perceptron networks and use it to select an optimal network architecture from a set of possible architectures. We also propose a heuri...