This research aims to clarify the concept of doctrinal rules and adjust its basic terminologies. It further aims to lay down a map for the method of rooting this science by mentioning its rooted sources, in addition to drawing a miniature picture of its history, origin, formation and development. The paper ends with practical models to highlight its importance in rooting the science of nodal rules and facilitating the mentioning of its scattered discussions in a short and comprehensive phrase. The study further illustrates the pioneering role of doctrinal rules science in managing the doctrinal disputes, combining multiple sayings, and in bringing together opposing opinions. The study follows the inductive, descriptive and analytical approach. The importance of the research topic lies in the fact that it tackles something that has not yet been widely examined. Thus, researching such a topic is considered a new thing due to the scarcity of what has been written on it, on the one hand. On the other hand, the topic is serious as it talks about the Contractual Rules, which have not gained sufficient research among the applicants. Besides, what has been so far written on the doctrinal rules is related to the chapters of the doctrine and its general discussions; a matter which is similar to Al-Ghazali’s rules of beliefs. No allocation was dedicated to its contractual aspect. Accordingly, the present research is one of the important building blocks of the doctrinal lesson, as it is related to inferencing the science of belief and collecting its dispersed discussions under general rules in an
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
... Show MoreIn this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria