基于BiLSTM代理模型的RFID标签天线快速多目标设计

为快速完成超高频(UHF)标签天线多目标设计,构建了基于双向长短期记忆(BiLSTM)神经网络的新型天线性能预测代理模型,并使用带精英策略的非支配排序遗传算法(NSGA-Ⅱ)配合静态惩罚对RFID标签天线进行多目标寻优.首先按照RFID标签天线延伸的趋势将天线结构序列化并依次输入BiLSTM网络结构,结合响应集训练出适...

Fast Multi-objective RFID Tag Antenna Design Based on BiLSTM Surrogate Model

In order to quickly complete the multi-objective design of ultrahigh frequency(UHF) tag antenna, a new antenna performance prediction surrogate model based on BiLSTM neural network is constructed in this paper, and the non-dominated sorting genetic algorithm with elite strategy (NSGA-II) is used to optimize the RFID tag antenna under static punishment. Firstly, the antenna structure is serialized and input into BiLSTM network in accordance with the trend of RFID tag antenna extension, and the surrogate model suitable for RFID tag antenna is developed in combination with response training. Further, in order to search all tag antenna forms within the feasible domain, especially the boundary of the feasible domain to the maximum extent, static penalty is introduced in NSGA-II algorithm to finally complete the rapid multi-target design of RFID tag antenna with low return loss, minification and broadband. The design example shows that the method is superior to the existing antenna design methods in terms of prediction accuracy and calculation cost, it has applicability and practical value.