A model for extrapolating the reality of investment in ICT in the Arab world using RBF

Abstract

With the passage of time, the development of computers and communication technologies, information and knowledge, information has become a major pillar of development and progress, and investments in information and communication technology constitute more than 50% of the gross domestic product of developed countries this is back to knowledge and convert it to information have a great values and benefits. The research represents a step to study the level of investment reached by the Arab countries in information and communication technology, and to identify the most important indicators that would improve the scientific, economic and development level in the Arab world, using the technology of artificial neural networks represented by the RBF network. The sample of study are the countries in Arab world and the data in of imports, exports and investment processed as  input to the network from  the years of 2006-2014, the model has adopted the style of gradient descending  error during testing and training. This research try to clarify the concept of the concept of ICT and its implications for investment, growth and development in the Arab world, as well as an explanation of the RBF network. While the practical side dealt with the construction of a forecasting model for the reality of investment in ICT exports and imports for the years 2006-2014 using the artificial nerve RBF network. The Matlab R2011a and Alyuda Neuron-Intelligence programs were used to implement the practical aspect. The RBF network proved its efficiency in determining the level Arab countries have reached an investment in ICTs as well as their efficiency in processing missing data.