Crosstalk Prediction in Twisted-Wire Pairs Based on Beetle Swarm Optimization Algorithm

In this paper, a new algorithm for predicting per unit length (p.u.l) parasitic parameters of transmission line is proposed. In the twisted-wire pair (TWP), different rotation degrees correspond to different parasitic parameters, which brings difficulties to the solution of telegraph equation. At present, the mainstream method is to divide TWP and use the cascade theory to solve each segment as a parallel transmission line. Therefore, we propose to use the beetle swarm optimization (BSO) algorithm to optimize the weights of the back propagation neural network, use a certain sample to train the network. This algorithm is used to predict the p.u.l parameters of uniform and non-uniform TWP, and the finite-difference time-domain (FDTD) method is used to solve telegraph equation. Among them, the crosstalk value of the uniform TWP is compared with the simulation value in the CST to verify the effectiveness of the proposed algorithm; the non-uniform TWP performs 500 random generation calculations to give the maximum envelope value of the crosstalk.