The determination of antenna geometric parameters is a major difficulty in the process of antenna design. With the progress of communication technology, the requirements of antenna performance are gradually improved, the design process of antenna becomes more complex to meet the performance requirements of engineering. As a mathematical model with strong information and data processing ability, artificial neural network (ANN) has been gradually applied to antenna parameters prediction and other related fields. In order to quickly and accurately obtain the model of high-performance L-shaped probe-fed patch antenna, an improved artificial bee colony (IABC) algorithm was proposed. The algorithm was improved to overcome the weak local optimization ability of standard artificial bee colony (ABC) algorithm. It can be seen from the experimental results that the IABC algorithm based on ANN is an effective optimization algorithm for microstrip antenna design optimization.

中文翻译：

---

基于人工神经网络的改进人工蜂群算法对L形探头馈电贴片天线S参数进行准确预测

天线几何参数的确定是天线设计过程中的一大难点。随着通信技术的进步，对天线性能的要求逐渐提高，天线的设计过程变得更加复杂，以满足工程的性能要求。人工神经网络(ANN)作为一种具有较强信息和数据处理能力的数学模型，已逐渐应用于天线参数预测等相关领域。为了快速准确地获得高性能L形探头馈电贴片天线模型，提出了一种改进的人工蜂群(IABC)算法。针对标准人工蜂群(ABC)算法局部优化能力弱的问题，对该算法进行了改进。