mean square error analysis
Statistical Features and Traditional SA SVM Classification Algorithm for Crack Detection
... feature analysis algorithm based on the com- bination of three damage indexes which are the differences of gradient, mean, mean square error between the healthy and non-healthy state of ...
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Motion Object Detection Using Mean Square Error Method
... it takes a simple picture of an image, this basic feature of CCTV has been studied extensively [3]. The most importance technique of this smart CCTV related research is to track and analyze objects the images[4]. Thus, ...
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Mean square error optimal weighting for multitaper cepstrum estimation
... ‘A’ of recorded data of the Swedish word Hallå (Hallo) as well as of the whole word Hallå from the same speakers (three males and three females). The reason for analyz- ing ‘A’ is the more stationary character of vowels ...
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Sentiment Analysis of Social Media Text Data using Back Propagation in Artificial Neural Networks
... It can be concluded from the mathematical background and subsequent results that the proposed system yields high accuracy for text mining data. The data used here are in the form of tweets. The training algorithm used is ...
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A COMPARATIVE ANALYSIS OF MEAN SQUARE ERROR ADAPTIVE FILTER ALGORITHMS FOR GENERATION OF MODIFIED SCALING AND WAVELET FUNCTION
... squared error (MSE), therefore the spatial filtering problem involves estimation of the signal s(n) from the received signal x(n) by minimizing the error between the reference signal d(n), which closely ...
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Comparative Analysis of the Efficiencies on Methods of Handling Multicollinearity in Regression Analysis
... Webster et al. ([W+76]), Latent root regression follows the same principle as the Principal Component Regression. In fact, it can be rightly referred to as an extension of Principal Component for examining alternative ...
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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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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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RMSE (Root Mean Square Error), respectively.
... In this research, our main objective was to find a model to efficiently forecast the electricity consumption in a household by applying Box and Jenkins method. The suitable forecasting methods were chosen for finding the ...
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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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IJCSMC, Vol. 6, Issue. 1, January 2017, pg.23 – 29 An Efficient Hybrid Approach for Secure Speech Cryptography
... comparative analysis of mean square error and peak signal to noise ratio parameters in case of RSA, DES and Hybridization algorithms concludes that The mean square error ...
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Hybrid fastslam approach using genetic algorithm and particle swarm optimization for robotic path planning
... the error occurs during estimation process. Root mean square error (RMSE) analysis is used to calculate the ...The error is calculated based on two indicators, ...RMSE ...
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Studies on amyloglucosidase from rhizopus delemar
... The standard error of a mean is obtained by dividing the square root of tho error variance standard deviation by the square root of the number of experimental points#... variance Is comp[r] ...
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Analysing the temporal dynamics of model performance for hydrological models
... with mean temperatures of 11 ◦ C and 1 ◦ C for the periods April–September and October–March, ...their analysis based on topography, soil types and land use that subsurface stormflow is likely to be the ...
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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 optimal prediction data for various ANN models were obtained by comparing with the parameter of error estimates such as Mean Absolute Error MAE, Mean Square Error MSE, Mean Absolute [r] ...
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A De Noising Method for Track State Detection Signal Based on EMD
... A De-Noising Method on EMD under Consecutive Mean Square Error Criterion The thought of a de-noising method on EMD under consecutive mean square error criterion is [14] [15], the first d[r] ...
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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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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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An Approach to Identify a Model for Efficient Prediction of Exchange Rates Using Setty Volatile Index (SVI)
... These models have been tested to predict currency exchange rate between US dollar Indian Rupees and Japanese Yen and also stock market data like US-RUPEE and IBM etc. The performances of the proposed models have been ...
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Call option price function in Bernstein polynomial basis with no arbitrage inequality constraints
... We propose an efficient method for the construction of an arbitrage-free call option price function from observed call price quotes. The no-arbitrage theory of option pricing places various shape constraints on the option ...
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