The method of solving volterra integral equation by using numerical solution is a simple operation but to require many memory space to compute and save the operation. The importance of this equation appeares new direction to solve the equation by using new methods to avoid obstacles. One of these methods employ neural network for obtaining the solution.
This paper presents a proposed method by using cascade-forward neural network to simulate volterra integral equations solutions. This method depends on training cascade-forward neural network by inputs which represent the mean of volterra integral equations solutions, the target of cascade-forward neural network is to get the desired output of this network. Cascade-forward neural
... Show MoreIn this work, some of numerical methods for solving first order linear Volterra IntegroDifferential Equations are presented. The numerical solution of these equations is obtained by using Open Newton Cotes formula. The Open Newton Cotes formula is applied to find the optimum solution for this equation. The computer program is written in (MATLAB) language (version 6)
In this paper, two meshless methods have been introduced to solve some nonlinear problems arising in engineering and applied sciences. These two methods include the operational matrix Bernstein polynomials and the operational matrix with Chebyshev polynomials. They provide an approximate solution by converting the nonlinear differential equation into a system of nonlinear algebraic equations, which is solved by using
In this paper, two meshless methods have been introduced to solve some nonlinear problems arising in engineering and applied sciences. These two methods include the operational matrix Bernstein polynomials and the operational matrix with Chebyshev polynomials. They provide an approximate solution by converting the nonlinear differential equation into a system of nonlinear algebraic equations, which is solved by using
Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi
... Show MoreIn this paper we study the effect of the number of training samples for Artificial neural networks ( ANN ) which is necessary for training process of feed forward neural network .Also we design 5 Ann's and train 41 Ann's which illustrate how good the training samples that represent the actual function for Ann's.
In today's world, most business, regardless of size, believe that access to Internet is imperative if they are going to complete effectively. Yet connecting a private computer (or a network) to the Internet can expose critical or confidential data to malicious attack from anywhere in the world since unprotected connections to the Internet (or any network topology) leaves the user computer vulnerable to hacker attacks and other Internet threats. Therefore, to provide high degree of protection to the network and network's user, Firewall need to be used.
Firewall provides a barrier between the user computer and the Internet (i.e. it prevents unauthor
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