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508 articles for “robust”

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Research ArticleOpen accessEvery word in the titleAn Empirical Study of Robust Modified Recursive Fits of Moving Average ModelsMohamed Ali Ismail, Hend A. Auda, Joe W. McKean, Mahmoud Mohamed SadekThe time-series Moving Average (MA) model is a nonlinear model; see, for example. For traditional Least Squares (LS) fits, there are several algorithms to use for computing its fit. Since the model is nonlinear, Fuller discusses a Newton-type step algorithm. proposed a recursive algorithm based on a sequence of three linear LS regressions. In this study, we robustify Koreisha and … …Journal of Mathematics and Statistics, Vol. 18, Issue 1 · 28 Jul 2022 · 5,859 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRobust Modelling of Coronavirus Cases in Egypt: Poisson INARCH and Negative Binomial INARCHHanan ElsaiedThis study compares robust Poisson INARCH(P) models (more briefly: RP-INARCH) and robust negative binomial INARCH(p) models (more briefly: RNB-INARCH) to fit the new daily confirmed cases for the first wave of COVID 19 in Egypt. The robust estimation of these models is based on some modifications of the Conditional Maximum Likelihood Estimates (CMLE). The simulation results show that RNB-INARCH is … …Journal of Mathematics and Statistics, Vol. 17, Issue 1 · 23 Jun 2021 · 7,116 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleCompressive Sensing Theory for Improving the Robustness and the Security of the Discrete Wavelet Transform-Singular Value Decomposition Watermarking SchemeRasha Shoitan, Sawsan Morkos GharghoryDigital watermarking has been suggested as a solution to protect copyright and ownership of digital images. The effective watermarking scheme should satisfy imperceptibility, robustness, capacity and security requirements. In this research, the security issue and the lack of reconstruction quality of the watermark logo of the integration of Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD) and Compressive Sensing (CS) … …Journal of Computer Science, Vol. 17, Issue 4 · 28 Apr 2021 · 6,599 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSolving the Robust Design Problem for a Two-Commodity Flow Network with Node FailureNoha Hamdy Radwan, Moatamad Refaat Hassan, Mohamed Eid HusseinThe robust design in a flow network is one of the most important problems. It is defined as searching the optimal capacity that can be assigned to the nodes such that the network still survived even under the node’s failure. This problem is considered NP-hard. So, this study presents a genetic-based algorithm to determine the maximum node capacity for a … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 4 · 28 Dec 2020 · 6,593 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleUsing Robust Statistics, Exploring Document Analysis and Gis for Defining and Localizing Geochemical Anomalies-Case Study in Sin Quyen Copper Mine, Lao Cai Province, Viet NamQuoc Lap Kieu, Huu Tap VanApplication of robust statistic and Exploratory Data Analysis (EDA) as well as the support of Geography Information System (GIS) for defining and assessing geochemical anomalies. The research was conducted in Sin Quyen copper mine, Lao Cai province, Viet Nam with 1,284 combination of aquatic sedimentary geochemical sample in scale of 1/200,000. The area of 5,717.8 km2 was chosen to make … …Current Research in Geoscience, Vol. 7, Issue 2 · 1 Aug 2017 · 8,404 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRobust Linear Discriminant AnalysisSharipah Soaad Syed Yahaya, Yai-Fung Lim, Hazlina Ali, Zurni OmarLinear Discriminant Analysis (LDA) is the most commonly employed method for classification. This method which creates a linear discriminant function yields optimal classification rule between two or more groups under the assumptions of normality and homoscedasticity (equal covariance matrices). However, the calculation of parametric LDA highly relies on the sample mean vectors and pooled sample covariance matrix which are sensitive … …Journal of Mathematics and Statistics, Vol. 12, Issue 4 · 4 Jan 2017 · 7,649 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRobust Diagnosis of a DC Motor by Bond Graph ApproachAbderrahmène Sallami, Nadia Zanzouri, Mekki KsouriIn this article, a Bond Graph (BG) approach is used for modeling, simulation and robust diagnosis of a DC Motor. The design and calculation of an observer is achieved by using graphical methods taking advantage of the structural properties of bond graph model. Simulation results are used to show the dynamic behavior of the system variables and assessing the performance … …American Journal of Engineering and Applied Sciences, Vol. 9, Issue 2 · 17 Jun 2016 · 8,001 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOn the Enlargement of Robust Region of Chaotic Tent Map for the Use in Key Based Substitution-Box (S-Box)Muhammad Asif Khan, Varun JeotiRobust chaotic maps with wide robust region are favored in cryptography as it extends the key length. Chaotic tent map has robust chaos for control parameter μ = 2. Perturbation of control parameter values beyond control parameter 2, results in orbit diverging towards infinity and trajectories vanish. Thus, to avoid trajectories diverging to infinity and to keep trajectories chaotic beyond … …Journal of Computer Science, Vol. 11, Issue 3 · 19 Apr 2015 · 6,934 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA ROBUST OPTIMIZATION APPROACH FOR INDEX TRACKING PROBLEMMohsen Gharakhani, Forough Zarea Fazlelahi, S. J. SadjadiIndex tracking is an investment approach where the primary objective is to keep portfolio return as close as possible to a target index without purchasing all index components. The main purpose is to minimize the tracking error between the returns of the selected portfolio and a benchmark. In this study, quadratic as well as linear models are presented for minimizing … …Journal of Computer Science, Vol. 10, Issue 12 · 26 Dec 2014 · 8,872 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleMODEL SELECTION VIA ROBUST VERSION OF R-SQUAREDShokrya SalehR-squared (R2) is a popular method for variable selection in linear regression models. R2 based on Least Squares (LS) regression minimizes the sum of the squared residuals; LS is sensitive to outlier observation. Alternative criterion based on M-estimators, which is less sensitive to outlying observation has been proposed. In this study explicit expression for such criterion is obtained when the … …Journal of Mathematics and Statistics, Vol. 10, Issue 3 · 9 Oct 2014 · 7,460 accessesView PDFCite