model mean square error
Process improvement to the anodize line through design of experiments
... Analysis of Variance 18 ANOVA of Freedom Degrees Sum of Squares Model, Error, Total Model, Error, Total Model Mean Square Error Mean Square F Ratio Prob>F "The analysis of variance obser[r] ...
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Statistical analysis on rainfall and discharge data : in study area in Johor river basin
... Best fitted model were analyze using statistical criteria of Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE) The best model used for forecasting the r[r] ...
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Air Temperature Prediction using Artificial Neural Network for Anyigba, North Central Nigeria
... prediction model. The Root Mean Square Error is then calculated between the perceptron and the desired output for the input ...proposed model is tested using the network of the hidden ...
6
New Criteria of Model Selection and Model Averaging in Linear Regression Models
... Abstract: Model selection is an important part of any statistical ...best model including frequentist and Bayesian ...particular model to be the best approximating model. Model ...
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ARIMA Modelling to Forecast and Analyze Indian Sectoral Stock Prices
... a model which will help understand how much past data must be used to forecast the peak demand on the days of the ...(root mean square error) and MAPE (mean absolute percentage ...
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Improvement of the Preliminary Test Estimator When Stochastic Restrictions are Available in Linear Regression Model
... The mean square error and scalar mean square error comparisons between PTSRLE and SRLE are carried out in Section ...Scalar Mean Square ...
10
Index Terms path loss model, path loss exponent, least
... prediction model, for GSM 900 MHz signals recorded in the sub urban region of Hyderabad city (Southern ...Hata model, ECC-33 model and SUI model are used to predict the path ...Hata ...
7
Biological Forum An International Journal 7(1): (2015)
... as mean monthly to the algorithm as input variables and monthly potential evapotranspiration months later, as the output variables, to the M5P algorithm were evaluated using “correlation coefficient”, “Root ...
5
Biometric Person Identification from 3D Ear Images and a Time Efficient Ear Shape Recognition
... a model shape by iteratively minimizing the distance between corresponding ...of model ears in 3D images are extracted and ...each model ear helix, we run the ICP algorithm to find the initial rigid ...
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A Comparative Study in Predicting Colon Rectum Cancer using Auto Regressive Integrated Moving Average (ARIMA) and Artificial Neural Network (ANN) Models
... the model is was modeled is designed by using two techniques for a period of 50 years (from 1960 to 2010) and the Mean Absolute Error (MAE), Mean Square Error (MSE), Mean ...
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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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Mean Square Error of Blind Channel Estimation Using a Constant Modulus Algorithm
... high error at the ...Least Square Estimation (LSE), Minimum Mean Square Error (MMSE) are based on single carrier system with pilot symbols for channel estimation to reduce the ...system ...
6
Analyzing Cervical Cancer by using an Ensemble Learning Approach based on Meta Classifier
... as Mean Absolute Logarithmic Error (MALE), Root Mean Square Logarithmic Error (RMSLE), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) ...
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Wavelet based Image Denoising using Weighted Highpass Filtering Coefficient and Exposure based Sub-Image Histogram Equalization Enhancement Technique
... ID model is that it should completely reduce noise as much as possible and edge ...quality. Mean Square Error (MSE), Root Mean Square Error (RMSE) and Peak Signal to Noise ...
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Mean Square Error of Prediction in the Bornhuetter-Ferguson Claims Reserving Method
... Poisson model in that the variance is not equal to the mean. This model was introduced for claims reserving in a Bayesian context by Verrall (1990, 2000, 2004) and Renshaw & Verrall (1998) and it ...
25
RMSE (Root Mean Square Error), respectively.
... a model to forecast the electricity consumption in a household and to find the most suitable forecasting period whether it should be in daily, weekly, monthly, or ...(Root Mean Square Error), ...
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Evaluation of the new UKCA climate-composition model – Part 2: The Troposphere
... annual mean bias, root mean square error, correlation co- efficient, and model score) are also included in the ...the model captures both the seasonal cycle and the absolute ...
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Sentiment Analysis of Social Media Text Data using Back Propagation in Artificial Neural Networks
... Abstract: Artificial Neural Networks have gained tremendous importance off late due to its large data handling and analyzing capability. One of the major areas of research that has been impacted by it is the field of ...
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The Implementation of Forecasting Method by Incorporating Human Judgment
... forecasting error that gives some impacts to inventory (occurring overstock and stock ...the error value when the forecaster decides the size of demand for the next ...
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Analysing the temporal dynamics of model performance for hydrological models
... The hillslope module of the physically based model Catflow (Zehe and Fluhler, 2001; Zehe and Bl¨oschl, 2004; Zehe et al., 2005) was used to model runoff generation in the Malalc- ahuello catchment. It ...
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