A Noisy Chaotic Neural Network Approach to Topological Optimization of a Communication Network with Reliability Constraints

نویسندگان

  • Lipo Wang
  • Haixiang Shi
چکیده

Network topological optimization in communication network is to find the topological layout of network links with the minimal cost under the constraint that all-terminal reliability of network is not less than a given level of system reliability. The all-terminal reliability is defined as the probability that every pair of nodes in the network can communicate with each other. The topological optimization problem is an NP-hard combinatorial problem. In this paper, a noisy chaotic neural network model is adopted to solve the all-terminal network design problem when considering cost and reliability. Two sets of problems are tested and the results show better performance compared to previous methods, especially when the network size is large.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Estimation of Network Reliability for a Fully Connected Network with Unreliable Nodes and Unreliable Edges using Neuro Optimization

In this paper it is tried to estimate the reliability of a fully connected network of some unreliable nodes and unreliable connections (edges) between them. The proliferation of electronic messaging has been witnessed during the last few years. The acute problem of node failure and connection failure is frequently encountered in communication through various types of networks. We know that a ne...

متن کامل

بهبود بازشناسی مقاوم الگو در شبکه های عصبی بازگشتی جاذب از طریق به کارگیری دینامیک های آشوب گونه

In this paper, two kinds of chaotic neural networks are proposed to evaluate the efficiency of chaotic dynamics in robust pattern recognition. The First model is designed based on natural selection theory. In this model, attractor recurrent neural network, intelligently, guides the evaluation of chaotic nodes in order to obtain the best solution. In the second model, a different structure of ch...

متن کامل

A Neural Network Method Based on Mittag-Leffler Function for Solving a Class of Fractional Optimal Control Problems

In this paper, a computational intelligence method is used for the solution of fractional optimal control problems (FOCP)'s with equality and inequality constraints. According to the Ponteryagin minimum principle (PMP) for FOCP with fractional derivative in the Riemann- Liouville sense and by constructing a suitable error function, we define an unconstrained minimization problem. In the optimiz...

متن کامل

An efficient modified neural network for solving nonlinear programming problems with hybrid constraints

This paper presents ‎‎the optimization techniques for solving‎‎ convex programming problems with hybrid constraints‎.‎ According to the saddle point theorem‎, ‎optimization theory‎, ‎convex analysis theory‎, ‎Lyapunov stability theory and LaSalle‎‎invariance principle‎,‎ a neural network model is constructed‎.‎ The equilibrium point of the proposed model is proved to be equivalent to the optima...

متن کامل

A New Method for Intrusion Detection Using Genetic Algorithm and Neural network

Abstract— In order to provide complete security in a computer system and to prevent intrusion, intrusion detection systems (IDS) are required to detect if an attacker crosses the firewall, antivirus, and other security devices. Data and options to deal with it. In this paper, we are trying to provide a model for combining types of attacks on public data using combined methods of genetic algorit...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004