mean square error values
A Comparative Study in Predicting Colon Rectum Cancer using Auto Regressive Integrated Moving Average (ARIMA) and Artificial Neural Network (ANN) Models
... the values in a time series as a linear combination of its own past values, past errors and current and past values by using the concept of time ...the Mean Absolute Error (MAE), ...
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Face Recognition By Using Eigen Face Method
... and Mean square error to match the random image with Eigen face ...the error values like Euclidean distance and Mean square ...
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Development of a Computer Aided System for Swine Flu Prediction using Computional Intelligence
... Root- mean-square error. As Root-mean-square error ought to be lower which implies algorithm is indicating the superior results when compared to access ...indicates ...
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Mean Square Error of Blind Channel Estimation Using a Constant Modulus Algorithm
... These results are justifiable in that the LS estimation assumes independent components of the frequency response which does not use the correlation properties of the channel making it sensitive to error. The ...
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Air Temperature Prediction using Artificial Neural Network for Anyigba, North Central Nigeria
... in error for future prediction. Also, Using the Root Mean Square Error (RMSE) as a means of comparison, the result shows that the model predictions are in good agreement with the values ...
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Photoplethysmography: Towards a non-invasive pressure measurement technique
... Figure 4 Typical scattergrams and curve fits for ln(P)-V functions using the different methods are presented. Panel (a) shows the natural logarithmic systolic pressure ln(Ps)- adjusted pulse volume (APV) function. Panel ...
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Mean square error optimal weighting for multitaper cepstrum estimation
... the Slepian multitapers. The Slepian multitapers, how- ever, have better leakage properties or out-of-band bias [8]. The sampling frequency of the actual process will effect an estimated ρ as well as the decision of the ...
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RMSE (Root Mean Square Error), respectively.
... The purpose of this research was to find a suitable model to forecast the electric consumption in a household, and to find the most suitable forecasting period (in daily, weekly, monthly, or quarterly). We used the ARIMA ...
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STAGE-DISCHARGE MODELING USING SUPPORT VECTOR MACHINES
... root mean square error (RMSE) values for different data sets (Tables 3 & 4) are used for the performance evaluation of the models and comparison of the results for establishing the ...
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Assessment of Breast Cancer Detection and Implementation
... of Mean Square Error Vs Scanned image using watershed segmentation ...higher values posses Cancer than that of the images with no ...the values obtained are lesser when compared with ...
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Performance and Analysis of Channel Estimation Techniques for LTE Downlink System under Fading with Mobility
... Least Square Error (LSE) and the Linear Minimum Mean Square Error (LMMSE) using QPSK and 16 QAM modulation techniques are studied and also studied the effect of channel length on the ...
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Theoretical and empirical estimates of mean-variance portfolio sensitivity
... of mean-variance portfolio weights in a market model with multiple risky assets and a riskless ...the mean square error are derived in the case when asset excess returns are multivariate ...
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Evaluation of growth stage specific crop coefficients of maize using weighing lysimeter
... Kc values by investigating water use of maize (Zea mays ...Kc values determined for maize during the growing season varied from ...evapotranspiration values were compared to assess the performance of ...
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Motion Object Detection Using Mean Square Error Method
... background image but it uses a 24-bit image with R, G, B values, and thus used grater capacity then that of FDM or BSM that only store luminance value. The method proposed in this study divide the total memory ...
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Re evaluation of individual diameter : height allometric models to improve biomass estimation of tropical trees
... estimated values, mean square error, and bias, of the main proposed DBH : H allometric models based on local data sets for three tropical forests: a lowland semi- deciduous forest in Panama, a ...
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Improvement of the Preliminary Test Estimator When Stochastic Restrictions are Available in Linear Regression Model
... When different estimators are available for the same parameter vector in the linear regression model one must solve the problem of their comparison. Usually as a simultaneous measure of covariance and bias, the ...
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Nonasymptotic bounds on the mean square error for MCMC estimates via renewal techniques
... Abstract The Nummellin’s split chain construction allows to decompose a Markov chain Monte Carlo (MCMC) trajectory into i.i.d. “excursions”. Regenerative MCMC algorithms based on this technique use a random number of ...
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
... 3.11 Linear vector quantization network architecture 70 4.1 Analysis of mean square error for 21 mother wavelets function 75 4.2 Analysis of signal to noise ratio for 21 mother wavelets function 77 ...
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A De Noising Method for Track State Detection Signal Based on EMD
... From Figure 3, the higher signal noise ratio (SNR), the de-noising effect is better; in low signal noise ratio (SNR), changed obviously after de-noising signal distortion. This shows that the de-noising method on EMD ...
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The Implementation of Forecasting Method by Incorporating Human Judgment
... The results of forecasting will translate to parameters that are used to determine inventory decisions. The better the performance of forecasting, the better the performance of the inventory system will result. The ...
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