نتایج جستجو برای: root mean square error rms and matlab
تعداد نتایج: 16903539 فیلتر نتایج به سال:
Analysis probative spatial data method for checking patterns spatial accidental and accidental is distribution variables spatial and correlation spatial from more usage and more important tools Analysis for is the research in the case spatial data. The aim in research, is evaluation operation methods find inside in distribution spatial land use city Kerman. That on base of methods find inside k...
Accurate measurement of ground reaction forces under discrete areas of the foot is important in the development of more advanced foot models, which can improve our understanding of foot and ankle function. To overcome current equipment limitations, a few investigators have proposed combining a pressure mat with a single force platform and using a proportionality assumption to estimate subarea s...
Changes in electromyographic (EMG) parameters are used to evaluate timing, amplitude, and fatigue of muscle actions during movement. Little published data describe the reliability and precision of multiple EMG parameters, how these parameters compare to one another, and how these parameters vary between muscles. The purpose of this study was to determine the reliability and precision of four EM...
Large umbrella space antennas are essential for communication, monitoring and observation of Earth and space objects. Despite investigations devoted to space antenna dynamics, the disturbance impulse shape effect on the root mean square error of spacecraft antenna reflecting surface has not been studied. This paper overcomes this gap describing disturbance impulse impact on root mean square err...
The most important aspect of any classifier is its error rate, because this quantifies its predictive capacity. Thus, the accuracy of error estimation is critical. Error estimation is problematic in small-sample classifier design because the error must be estimated using the same data from which the classifier has been designed. Use of prior knowledge, in the form of a prior distribution on an ...
The problem of accurate dose accumulation in fractionated radiotherapy treatment for highly deformable organs, such as bladder, has garnered increasing interest over the past few years. However, more research is required in order to find a robust and efficient solution and to increase the accuracy over the current methods. The purpose of this study was to evaluate the feasibility and accuracy o...
This paper has two aims. The first is forecasting inflation in Iran using Macroeconomic variables data in Iran (Inflation rate, liquidity, GDP, prices of imported goods and exchange rates) , and the second is comparing the performance of forecasting vector auto regression (VAR), Bayesian Vector-Autoregressive (BVAR), GARCH, time series and neural network models by which Iran's inflation is for...
This paper reviews the development of a root mean squared error (RMS) flaw sizing criterion. The effect of using an RMS error criterion for the sizing performance of the PISC II [1-3] inspection teams is investigated. A crucial part of establishing an RMS error sizing criterion is the decomposition of the components in the RMS error into the sum of the squares of the mean error, the standard er...
The goal of the present study is to quantify and reduce, when possible, errors in two-dimensional digital particle image velocimetry (DPIV). Two major errors, namely the mean bias and root-mean-square (RMS) errors, have been studied. One fundamental source of these errors arises from the implementation of cross correlation (CC). Other major sources of these errors arise from the peak-finding sc...
The optimum design of solar energy systems strongly depends on the accuracy of solar radiation data. However, the availability of accurate solar radiation data is undermined by the high cost of measuring equipment or non-functional ones. This study developed a feed-forward backpropagation artificial neural network model for prediction of global solar radiation in Makurdi, Nigeria (7.7322 N lo...
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