RESUMEN
In real-life situations, we have to analyze the data that contains the atypical observations, and the presence of outliers has adverse effects on the performance of ordinary least square estimates. In this situation, redescedning M-estimators, proposed by Huber (1964), are used to tackle the effects of outliers to increase the efficiency of least square estimates. In this study, we introduce a redescending M-estimator designed to generate robust estimates by mitigating the influence of outlier observations, even when the tuning constant is set to low values. This innovative estimator exhibits enhanced linearity at its core and maintains continuity throughout its range. Our proposed estimator stands out for its novelty, simplicity, differentiability, and practical applicability across real-world scenarios. The results of the proposed redescedning M-estimators are compared with existing robust estimators using an extensive simulation study. Two examples based on real-life data are also added to validate the performance of the suggested function. The formulated redescedning M-estimator produced efficient results as compared to all the considered redescedning M-estimators.
RESUMEN
Many industrial applications, including coating processes, roller bearing uses, and cooling gas turbine rotors, involve non-Newtonian fluid flow across rotating cylinders. The current study aims at evaluating the energy transport of the Maxwell fluid rotating over a horizontal cylindrical surface using the Cattaneo-Christov heat flux conduction model. This model predicts the properties of thermal relaxation by revising conventional Fourier's law. Isothermal cubic autocatalytic kinetics provides a homogeneous reaction, while first-order kinetics yields a heterogeneous reaction. With the help of transformations, the system of ODEs relating the equations for energy, momentum, and concentration is produced. For a numerical solution, the bvp4c scheme, which is based on the finite difference technique in Matlab 9.7 R2019b, is used. The importance of dominant parameters is displayed with the graphical depictions for axial, radial, and azimuthal flows, as well as temperature and concentration distributions. The noteworthy results illustrate that the Maxwell parameter has a declining influence on all velocity components. Further, thermal relaxation time causes a decline in the temperature field as well. Moreover, as the homogeneous-heterogeneous reaction parameters are increased, a reduction in fluid concentration is shown.
RESUMEN
Measurement error (M.E) can have a substantial impact on quality control applications, diminishing the sensitivity to detect changes in the mean or variance of quality characteristics. To monitor shifts in process mean and dispersion, Exponentially Weighted Moving Average (EWMA) and Cumulative Sum (CUSUM) control charts are commonly employed. In our research, we investigated the influence of M.E on the Triple Exponentially Weighted Moving Average (TEWMA) control chart. We assessed the performance of the control chart using Average Run Length (ARL) as the evaluation metric. To compute the ARL properties, we adopted the Monte-Carlo simulation method. A comparison section has been made to check the performance efficiency of the control chart with the existing EWMA control chart. The implementation of a control chart on a real data set is also presented.
RESUMEN
Weight determining of attributes is an important factor in decision support systems since it corresponds to the relative importance of each criteria which is necessary to be determined since all the attributes aren't equally important. The aim of this paper is to put forward a method for multi Criteria decision making (MCDM) problems based on three trapezoidal fuzzy numbers under completely unknown weights environment. Based on the idea that the attribute with a larger deviation value among alternatives should be assigned a larger weight, an optimization model based on maximizing deviation method is established. F-OWA is considered to be vastly superior from the existing operators which usually take into account only the relative significance of decision makers. F-OWA operator considers not only the ratings of attribute values but also their ordered position that is it not only signifies the decision makers but also values the individual assessments. We utilize fuzzy ordered weighted averaging (F-OWA) operator to compute the collective overall preference value of each alternative and select the most desirable one according to their expected score values. The presented method is more generalized since we have used TTFNs, which are more effective in capturing uncertainty than IT2FS, just like triangular fuzzy numbers have a better representational power than simple interval numbers. Moreover, an illustrative example is given for the justification of the proposed technique.