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173 articles for “mean square”
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Research ArticleOpen accessIn the abstractConvSVD++: A Hybrid Deep CF Recommender Model using Convolutional Neural NetworkMohamed Grida, Lamiaa Fayed, Mohamed HassanRecommender systems are powerful systems that give added value to business and corporation. They are relatively recent technology and they will only keep improving in the future. The most widely used algorithms for recommender systems are categorized into the traditional recommender and deep-based recommender system. The traditional recommendation algorithm suffers from sparse data that significantly degrades recommendation accuracy. The hybrid … …Journal of Computer Science, Vol. 16, Issue 12 · 13 Jan 2021 · 6,736 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Study on the Effects of Non-Normality on the Performances of Max-DEWMA Versus SS-DEWMA ChartsTeh Sin Yin, Michael Khoo Boon ChongProblem statement: The called the Sum of Squares Double Exponentially Weighted Moving Average (SS-DEWMA) chart which is effective in detecting shifts in the mean and/or variance is compared with the Max-DEWMA (called the maximum double exponentially weighted moving average) chart. The comparison is based on the assumption that the distribution of the quality characteristic of the process is normal or … …Journal of Mathematics and Statistics, Vol. 8, Issue 1 · 18 Jan 2012 · 7,191 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Neural Network Based Model for Forecasting Sugar Cane ProductionO. O. Obe, D. K. ShangodoyinProblem statement: The global need for alternative energy source has necessitated the exploration of vast organic agricultural products with a view of processing them for the production of ethanol in commercial quantity. To ascertain a sustainable production of ethanol from processed sugar cane, a predictive model based on non-linearity nature of its production is imperative. This is due to unavailability … …Journal of Computer Science, Vol. 6, Issue 4 · 30 Apr 2010 · 7,272 accessesView PDFCite
Research ArticleOpen accessIn the abstractLinear Regression Model Selection Based on Robust Bootstrapping TechniqueHassan S. Uraibi, Habshah Midi, Bashar A. Talib, Jabar H. YousifProblem statement: Bootstrap approach had introduced new advancement in modeling and model evaluation. It was a computer intensive method that can replace theoretical formulation with extensive use of computer. The Ordinary Least Squares (OLS) method often used to estimate the parameters of the regression models in the bootstrap procedure. Unfortunately, many statistics practitioners are not aware of the fact that … …American Journal of Applied Sciences, Vol. 6, Issue 6 · 30 Jun 2009 · 7,880 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligence System for Software Maintenance Severity PredictionParvinder Singh Sandhu, Sunil Kumar, Hardeep SinghThe software industry has been experiencing a software crisis, a difficulty of delivering software within budget, on time, and of good quality. This may happen due to number of defects present in the different modules of the project that may require maintenance. This necessitates the need of predicting maintenance urgency of the particular module in the software. In this paper, … …Journal of Computer Science, Vol. 3, Issue 5 · 31 May 2007 · 6,947 accessesView PDFCite
Research ArticleOpen accessIn the abstractTwo-Stage Estimation in Inverse Problems using Combined Wavelet Thresholding and Penalized Maximum LikelihoodRobert G Aykroyd, Hassan AljohaniInverse problems occur in a wide range of practical scientific investigations where the variables of interest are only observed indirectly, such as magnetic and seismic imaging in geophysics, electrical tomography in industrial process monitoring, or PET scanning in medicine. Linear inverse problems can be thought of as highly multivariate regression problems with strong multicollinearity where the aim is to interpret … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 29 Sep 2017 · 7,928 accessesView PDFCite
Research ArticleOpen accessIn the abstractMedical Images Registration based on Normalized Dissimilarity IndexAmina KHARBACH, Mouad EL OMARI, Amar MARDANI et al.Image registration is an essential step in a large number of processing chains for medical images. It is used to align two images taken at different times and from different sensors as well. In this paper, we are interested in the rigid registration and similarity measures. We describe a new registration approach, based on the normalized dissimilarity index that results … …Journal of Computer Science, Vol. 13, Issue 9 · 28 Sep 2017 · 7,530 accessesView PDFCite
Research ArticleOpen accessIn the abstractDenoising Methods for MRI ImagerySamuel KozaitisThere are several new denoising algorithms that may be useful for magnetic resonance imaging. We compared the performance of some of the latest denoising algorithms with those that have been developed specifically for MRI imagery. We found that the latest approaches show impressive performance in terms of mean squared error, but a measure based on perceptual quality may be needed … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 3 · 30 Aug 2017 · 7,482 accessesView PDFCite
Research ArticleOpen accessIn the abstractSparse Sliced Inverse Quantile RegressionAli Alkenani, Tahir R. DikheelThe current paper proposes the sliced inverse quantile regression method (SIQR). In addition to the latter this study proposes both the sparse sliced inverse quantile regression method with Lasso (LSIQR) and Adaptive Lasso (ALSIQR) penalties. This article introduces a comprehensive study of SIQR and sparse SIQR. The simulation and real data analysis have been employed to check the performance of … …Journal of Mathematics and Statistics, Vol. 12, Issue 3 · 10 Sep 2016 · 7,133 accessesView PDFCite
Research ArticleOpen accessIn the abstractEstimation for Unknown Parameters of the Burr Type-XII Distribution Based on an Adaptive Progressive Type-II Censoring SchemeMontaser M. AmeinIn this study, the Maximum Likelihood Estimation (MLE) and Bayes estimation are exploited to make interval estimation based on adaptive progressive Type-II censoring for the Burr Type-XII distribution. Explicit form for the parameters of Bayes estimator doesn’t exist, so, Markov Chain Monte Carlo (MCMC) method is used as approximation to find posterior mean under squared error loss function. Real data … …Journal of Mathematics and Statistics, Vol. 12, Issue 2 · 29 Apr 2016 · 7,310 accessesView PDFCite