In real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson” and the “Expectation-Maximization” techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function i

Wind energy is becoming one of the renewable energy that has attracted great attention all over the world. This research work aims to build a map by which the user can have a thought about the number of generation hours of electricity from wind through all the year at the location of study (Wasit-Iraq). To interact the idea, this study included using the work included using different wind turbines at different heights. The results show that Gamesa G58-850 KW wind turbine gives more generated hours at 50 meters height.

Optimization procedures using a variety of input parameters have gotten a lot of attention, but using three non-edible seed oils of Jatropha (Jatropha curcas), Sesame (Sesamum indicum), and Sweet Almond (Prunusamygdalus dulcis) has a few advantages, including availability and non-food competitiveness. Optimizing a two-stage trans-esterification process using a sodium hydroxide-based catalyst at a fixed catalyst (1.0wt %) and temperature (60 ^oC) while varying molar ratio (1:3, 1:6, 1:12),  time (20–60 min), and mixing speed (500–1000 rpm), to produce optimal responses of yields were studied using response surface methodology (RSM). The optimization solution of molar ratio (1:3), time (40.9 min.),

The 3-parameter Weibull distribution is used as a model for failure since this distribution is proper when the failure rate somewhat high in starting operation and these rates will be decreased with increasing time .

In practical side a comparison was made between (Shrinkage and Maximum likelihood) Estimators for parameter and reliability function using simulation , we conclude that the Shrinkage estimators for parameters are better than maximum likelihood estimators but the maximum likelihood estimator for reliability function is the better using statistical measures (MAPE)and (MSE) and for different sample sizes.

Note:- n_s : small sample ; n_m=median sample

      We have designed, fabricated and studied the vertical axis wind turbine and its characterization. The system has been locally designed to pump water. It is considered as a one of the best options for low speed wind. The turbine has eight blades , each blade is 1.8m in length,  and the area dimension of the turbine 3.6 m² . were investigated  the  best characterization of the system at low wind speed are Power turbine  depends on the wind speed. It was 280 Watt at 6m/s and 160 watt at 5m/s  , and  the power after the turbine decreasing to factor  1/3. The system torque was 20 N.m , Power coefficient cap  0.29 , Tip speed ratio 0.46. It is suitable to be used in Iraq region , and low cost for get the wat

The aim of most researchers is to complete full projects for establishing renewable sources stations. The project depend on many variables, which is called criteria, that’s makes the project workable or not. The criterion which studied in this paper is roads suitability for transporting turbines from the loading ports to construction site. One of the important factors which must provide paved roads for transportation and within standard. Southern Um-Qasr port is the best choice to receive wind turbine equipments. The nods down to the construction region will face 0 turns, 2 bridges that crosses over and 23 bridges that passes underneath.

In multivariate survival analysis, estimating the multivariate distribution functions and then measuring the association between survival times are of great interest. Copula functions, such as Archimedean Copulas, are commonly used to estimate the unknown bivariate distributions based on known marginal functions. In this paper the feasibility of using the idea of local dependence to identify the most efficient copula model, which is used to construct a bivariate Weibull distribution for bivariate Survival times, among some Archimedean copulas is explored. Furthermore, to evaluate the efficiency of the proposed procedure, a simulation study is implemented. It is shown that this approach is useful for practical situations and applicable fo

Most of the Weibull models studied in the literature were appropriate for modelling a continuous random variable which assumes the variable takes on real values over the interval [0,∞]. One of the new studies in statistics is when the variables take on discrete values. The idea was first introduced by Nakagawa and Osaki, as they introduced discrete Weibull distribution with two shape parameters q and β where      0 < q < 1 and b > 0. Weibull models for modelling discrete random variables assume only non-negative integer values. Such models are useful for modelling for example; the number of cycles to failure when components are subjected to cyclical loading. Discrete Weibull models can be obta