关键词: 人工智能, 雷场网络, 斯坦纳树, 蛙跳优化, 离散量子粒子群优化

Abstract:

Due to the harsh battlefield surroundings and violent nature of intelligent minefield network applications, the minefield network sometimes suffers a largescale damage that involves several nodes and would thus create multiple disjoint partitions. A novel strategy for repairing such damage was investigated by modeling this problem as Steiner minimum tree problem. At first, a grid model of minefield area that limits the search space to a more manageable size was proposed. And then, according to combinated optimization algorithm of quantum discrete particle swarm optimization(QDPSO) and jumping frogs optimization(JFO), the position of relay nodes was confirmed and the minefield network was repaired. The simulation results demonstrate the effectiveness of the proposed recovery algorithm which has less computational time. Compared with the other algorithms, the proposed algorithm obtains more promising results in the average path length and the network life cycle.

Key words: artificial intelligence, minefield network, Steiner tree, jumping frogs optimization, quantum discrete particle swarm optimization