‎Financial market modeling and prediction is a difficult problem and drastic changes of the price causes nonlinear dynamic that makes the price prediction one of the most challenging tasks for economists‎. ‎Since markets always have been interesting for traders‎, ‎many traders with various beliefs are highly active in a market‎. ‎The competition among two agents of traders‎, ‎namely trend follo...

The presence of part-through cracks with limited length is one of the prevalent defects in the plate structures. Due to the slight effect of this type of damages on the frequency response of the plates, conventional vibration-based damage assessment could be a challenging task. In this study for the first time, a recently developed state-space method which is based on the chaotic excitation is ...

Cross-validation was originally invented to estimate the prediction error of a mathematical modelling procedure. It can be shown that cross-validation estimates the prediction error almost unbiasedly. Nonetheless, there are numerous reports in the chemoinformatic literature that cross-validated figures of merit cannot be trusted and that a so-called external test set has to be used to estimate ...

Motion segmentation is traditionally coupled with motion detection, where each image region corresponds to a particular motion model which accounts for the temporal changes in the region. Using the motion model to estimate the second frame from the rst frame, for example, should give a very low prediction error in the corresponding region. To relax the need for accurate motion models, it is pro...

The traditional multi-step ahead prediction is based on sequential algorithm to run multi-step ahead prediction and it brings error propagation problem. Furthermore, the prediction error of multi-step ahead includes both system and propagation errors. Therefore, how to decrease the propagation error has become an important issue in multi-step ahead prediction. In this study we had used the para...

a quantitative structure-activity relationship (qsar) study was conducted for the prediction of inhibitory activity of 1-phenyl[2h]-tetrahydro-triazine-3-one analogues as inhibitors of 5-lipoxygenase. the inhibitory activities of the 1-phenyl[2h]-tetrahydro-triazine-3-one analogues modeled as a function of molecular structures using chemometrics methods such as multiple linear regression (mlr) ...

Wind power prediction of wind farm plays a decisive role in stable electric power system operation.The BP neural network’s basic principle was introduced, and the numerical weather prediction (NWP) data and power data of wind farm as the training data of BP neural network was selected and trained; a linear regression model about the sample prediction error was presented, which considers the cou...

In this paper, we obtain  Bayesian prediction intervals as well as Bayes predictive estimators under square error loss for generalized order statistics when the distribution of the underlying population belongs to a family which includes several important distributions.

Models of associative learning have proposed that cue-outcome learning critically depends on the degree of prediction error encountered during training. Two experiments examined the role of error-driven extinction learning in a human causal learning task. Target cues underwent extinction in the presence of additional cues, which differed in the degree to which they predicted the outcome, thereb...