In this paper, some estimators for the reliability function R(t) of Basic Gompertz (BG) distribution have been obtained, such as Maximum likelihood estimator, and Bayesian estimators under General Entropy loss function by assuming non-informative prior by using Jefferys prior and informative prior represented by Gamma and inverted Levy priors. Monte-Carlo simulation is conducted to compare the performance of all estimates of the R(t), based on integrated mean squared.

The performance of a condenser in a domestic refrigerator system without wires and a condenser with a novel design consisted of number of loops as elliptical shape is investigated experimentally in this work. The experiment was conducted with a refrigerator designed to work with HFC134a, under no load and with loads of (1.5,3 and 12 liters of water). In particular, the effects of shape change of the condenser were very important in heat transfer enhancement and reduce of the frictional loss as a result of reducing the pressure drop in the condenser. The results shown that compressor work decreases with elliptical condenser about (8.6% to 11.3%), and then the power consumption decreases also. The performance of household refrigerator with

This study aimed to investigate the role of Big Data in forecasting corporate bankruptcy and that is through a field analysis in the Saudi business environment, to test that relationship. The study found: that Big Data is a recently used variable in the business context and has multiple accounting effects and benefits. Among the benefits is forecasting and disclosing corporate financial failures and bankruptcies, which is based on three main elements for reporting and disclosing that, these elements are the firms’ internal control system, the external auditing, and financial analysts' forecasts. The study recommends: Since the greatest risk of Big Data is the slow adaptation of accountants and auditors to these technologies, wh

Everybody is connected with social media like (Facebook, Twitter, LinkedIn, Instagram…etc.) that generate a large quantity of data and which traditional applications are inadequate to process. Social media are regarded as an important platform for sharing information, opinion, and knowledge of many subscribers. These basic media attribute Big data also to many issues, such as data collection, storage, moving, updating, reviewing, posting, scanning, visualization, Data protection, etc. To deal with all these problems, this is a need for an adequate system that not just prepares the details, but also provides meaningful analysis to take advantage of the difficult situations, relevant to business, proper decision, Health, social media, sc

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application

Research deals the crises of the global recession of the facets of different and calls for the need to think out of the ordinary theory and find the arguments of the theory to accommodate the evolution of life, globalization and technological change and the standard of living of individuals and the size of the disparity in income distribution is not on the national level, but also at the global level as well, without paying attention to the potential resistance for thought the usual classical, Where the greater the returns of factors of production, the consumption will increase, and that the marginal propensity to consume may rise and the rise at rates greater with slices of low-income (the mouths of the poor) wi

In this paper, simulation studies and applications of the New Weibull-Inverse Lomax (NWIL) distribution were presented. In the simulation studies, different sample sizes ranging from 30, 50, 100, 200, 300, to 500 were considered. Also, 1,000 replications were considered for the experiment. NWIL is a fat tail distribution. Higher moments are not easily derived except with some approximations. However, the estimates have higher precisions with low variances. Finally, the usefulness of the NWIL distribution was illustrated by fitting two data  sets

Tourism plays an important role in Malaysia’s economic development as it can boost business opportunity in its surrounding economic. By apply data mining on tourism data for predicting the area of business opportunity is a good choice. Data mining is the process that takes data as input and produces outputs knowledge. Due to the population of travelling in Asia country has increased in these few years. Many entrepreneurs start their owns business but there are some problems such as wrongly invest in the business fields and bad services quality which affected their business income. The objective of this paper is to use data mining technology to meet the business needs and customer needs of tourism enterprises and find the most effective