Systems, Man, and Cybernetics

 

Home

• [P1115] Saving the calculating time of the TCNN with nonchaotic simulated annealing strategy
  Author(s): Zhenning Wang
  
  

  Abstract
  Transient Chaotic Neural Networks (TCNNs) and Noisy Chaotic Neural Networks(NCNNs) have been proved their searching abilities for solving combinatorial optimization problems(COPs). The chaotic dynamics of the TCNN and the NCNN are believed to be important for their searching abilities. However, in this paper, we propose that we cut off the rich dynamics such as periodic and chaotic attractors in the TCNN and just utilize the nonchaotic converge dynamics of the TCNN to save the time needed for computations. The new strategy is named nonchaotic simulated annealing (NCSA). Experiments on the traveling salesman problems shows that NCSA is effective and saves over half of the time needed for computations.

  
   

Full Text (PDF)