Exponential smoothing technique is one of the most important quantitative techniques in forecasting. The accuracy of forecasting of this technique depends on exponential smoothing constant. Choosing an appropriate value of exponential smoothing constant is very crucial to minimize the error in forecasting. This paper addresses the selection of optimal value of exponential smoothing constant to ...

A method of predicting two forest stand structure attrithe ability of the regression equations to predict the stem butes, basal area and aboveground biomass, from meamap plot’s stand structure attributes was then evaluated. surements of forest vertical structure was developed and The QMCH was found to explain the most variance in tested using field and remotely sensed canopy structure the chron...

convolution each of the BOLD responses with a single universal transfer function, modeled BOLD signals were generated which when differenced with the measured BOLD signals showed residual signals which were smaller than the measurement uncertainty. The root mean square (RMS) of the residual signal (left number) was compared with the averaged standard deviation (SD) of the measured data (right n...

Nonparametric kernel estimators are mostly used in a variety of statistical research fields. Nadaraya-Watson estimator (NWK) is one the most important nonparametric that often regression models with fixed bandwidth. In this article, we consider four new Proposed Adaptive Kernel Regression Estimators (Interquartile Range, Standard Deviation, Mean Absolute Devotion, and Median Deviation) rather t...

We present the Generalized Root Mean Square Deviation (G-RMSD) method. G-RMSD is an optimization method to calculate minimal RMSD value of two atomic structures by optimal superimposition. not restricted systems with equal number atoms compare or a unique atom mapping between molecules. The can handle any type chemical structure, including transition states and which cannot be explained only va...