The study was reflection of the impact of the widespread use of polymer Novolak composite reinforced Glass fiber and Asbestos fiber once again with weight fraction 60% on the physical properties, which included (Hardness, Compressive deformation, compressive modulus of elasticity, Flexural modulus of elasticity, Resilience modulus, the maximum of Flexural strength, Flexural strain energy and Shear strength inner layers); it is known how much important the media as a source of bacterial contamination, which contributes directly or indirectly in the process of aging of these materials. These Novolak composite reinforced, prepared by weight fraction of (10%) and (14%) of the Hexamethylene-tetraamine (HMTA) hardener material. It showed the results of the comparison, the composite prepared to offer bacterial media, negatively effect on Hardness, Compressive strengths, Flexural strength and Flexural strain stored energy The research also concluded clear results, which is that there is the possibility to delay the aging process of the presence of bacterial circles, using glass fibers in the polymer Novolak composite reinforced, more than it is the use of asbestos fiber. And increase the weight fraction of hardener material to be 14%, coefficient of resilience reversal less than it is in the rest of the models, which leads to raise the value of the work done at the end of proportionality.
Time series have gained great importance and have been applied in a manner in the economic, financial, health and social fields and used in the analysis through studying the changes and forecasting the future of the phenomenon. One of the most important models of the black box is the "ARMAX" model, which is a mixed model consisting of self-regression with moving averages with external inputs. It consists of several stages, namely determining the rank of the model and the process of estimating the parameters of the model and then the prediction process to know the amount of compensation granted to workers in the future in order to fulfil the future obligations of the Fund. , And using the regular least squares method and the frequ
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The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin
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