This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

Abstract

                  The study aimed to prepare a practical guide for procedures for auditing the strategies of municipal institutions in achieving sustainable development by adopting the idea of ​​the audit matrix through which a classified report is prepared according to the dimensions of sustainable development, by preparing a specialized audit program for the purpose of auditing strategies for achieving sustainable development and emptying the results of the application of each of the paragraphs The program in the audit matrix that was prepared for the purpose of determining the impact of each observation and linkin

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

The concept of privatization is built on the basis of the transfer of assets and services of the public sector to the private sector this concept has appeared in the eighties of the last century whene the high oil prices took place and recession solution swept the world Which called for the freedom of the market and left the room for the private sector to take the initiatine in economic activity.         Both the IMF have   adopted this thesis in their programs of the structural adjustment in light of external and internal factors helped to Create the conditions to accept thesis that under the pretext of achieving a number of economic goals.

In Iraq in spite of

The research studies the sculptural formation in the third millennium: styles and trends, by taking the most important results of sculpture in the third millennium. The problem of the research is to search for the new sculptural formation in what it constitutes of social and human importance, and what are the important factors in forming the   contemporary sculptural structure, and what is the mechanism of showing and producing the new formation. The research requires the study of the most important thing that the (sculptural formation in the third millennium styles and trends) represents. The importance of research depends on the importance of the sculptural formation after the twentieth century and the importance that the for

The research aims to identify the most important concerns that led to the increase of  interest in the topic of corporate governance and specifically highlighting  the role of the audit committees of the Administration  Board in reducing the risk of the auditor and the rationalization of professional judgments، in particular about accepting  the assignment and setting the fees of the audit process by extrapolating  global experience in this area ، and a field study is conducted for a sample of private Iraqi banks to evaluate the role of audit committees constituted currently per with bank law no. (94) of 2004 and to be acknowledged with actual performance of these committees and their role in recommending the n

In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi