In this paper, a procedure to establish the different performance measures in terms of crisp value is proposed for two classes of arrivals and multiple channel queueing models, where both arrival and service rate are fuzzy numbers. The main idea is to convert the arrival rates and service rates under fuzzy queues into crisp queues by using graded mean integration approach, which can be represented as median rule number. Hence, we apply the crisp values obtained to establish the performance measure of conventional multiple queueing models. This procedure has shown its effectiveness when incorporated with many types of membership functions in solving queuing problems. Two numerical illustrations are presented to determine the validity of the procedure in this queueing model, which involved using trapezoidal and hexagonal fuzzy numbers. It can be concluded that graded mean integration approach is efficient with fuzzy queueing models to convert fuzzy queues into crisp queues. This finding has contributed to the body of knowledge by suggesting a new procedure of defuzzification as another efficient alternative.
The effect of White Place Image ( Test Image ) A4 has been studied as a function of luminous intensity using the t tu un ng gs st te en n l la am mpp and web camera enet. It was found that the tungsten lamp gives almost even intensities for the three color band and lighting composite at low voltage .while at high voltage causes a fare from each other . The statistical characteristic(mean and stander deviation ) results for three colors composites RGB and lighting composites L showed that the mean and stander deviation increases with the increase of voltage possibly owing to the increase image resolution, which reflects the value of stander deviation for the blue band
... Show MoreDatabase is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r
... Show MoreIn this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo
... Show MoreSliding Mode Controller (SMC) is a simple method and powerful technique to design a robust controller for nonlinear systems. It is an effective tool with acceptable performance. The major drawback is a classical Sliding Mode controller suffers from the chattering phenomenon which causes undesirable zigzag motion along the sliding surface. To overcome the snag of this classical approach, many methods were proposed and implemented. In this work, a Fuzzy controller was added to classical Sliding Mode controller in order to reduce the impact chattering problem. The new structure is called Sliding Mode Fuzzy controller (SMFC) which will also improve the properties and performance of the classical Sliding Mode control
... Show MoreThis paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima
... Show MoreThe main objective of this study is to measure the Impact of global financial crisis on some indicators of the Saudi Arabia's economy using the Mendel-Fleming model, the importance of the study applied by focusing on the theme of general equilibrium in the face of fluctuations in the global economy. Study used a descriptive approach and the methodology of econometrics to construct the model. Study used Eviews Program for data analysis. The Data was collected from the Saudi Arabian Monetary Agency, for the period (1997-2014).Stationery of the variables was checked by Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) unit roots tests. And also the co-integration
... Show MoreThis paper deals with constructing a model of fuzzy linear programming with application on fuels product of Dura- refinery , which consist of seven products that have direct effect ondaily consumption . After Building the model which consist of objective function represents the selling prices ofthe products and fuzzy productions constraints and fuzzy demand constraints addition to production requirements constraints , we used program of ( WIN QSB ) to find the optimal solution
In previous our research, the concepts of visible submodules and fully visible modules were introduced, and then these two concepts were fuzzified to fuzzy visible submodules and fully fuzzy. The main goal of this paper is to study the relationships between fully fuzzy visible modules and some types of fuzzy modules such as semiprime, prime, quasi, divisible, F-regular, quasi injective, and duo fuzzy modules, where under certain conditions it has been proven that each fully fuzzy visible module is fuzzy duo. In addition, there are many various properties and important results obtained through this research, which have been illustrated. Also, fuzzy Artinian modules and fuzzy fully stable modules have been introduced, and we study the rel
... Show MoreThe development that solar energy will have in the next years needs a reliable estimation of available solar energy resources. Several empirical models have been developed to calculate global solar radiation using various parameters such as extraterrestrial radiation, sunshine hours, albedo, maximum temperature, mean temperature, soil temperature, relative humidity, cloudiness, evaporation, total perceptible water, number of rainy days, and altitude and latitude. In present work i) First part has been calculated solar radiation from the daily values of the hours of sun duration using Angstrom model over the Iraq for at July 2017. The second part has been mapping the distribution of so