论文标题
通过两个计算智能模型预测太阳能活动（一项比较研究）
Forecasting Solar Activity with Two Computational Intelligence Models (A Comparative Study)
论文作者
论文摘要
太阳活动至关重要的是，准确预测太阳能活动，以减少大型高强度太阳喷发的电子设备的合理损害。最近，我们提出了钟楼（基于大脑的模糊推理系统）作为预测混乱系统的工具。钟楼的结构是基于恐惧调节的神经结构而设计的。通过将自适应网络分配给钟楼结构的组件，可以实现钟声的功能。本文尤其侧重于通过预测太阳能循环16至24的钟声评估作为预测因子的性能评估。将钟楼的性能与用于此目的的其他计算模型进行了比较，尤其是与自适应的神经模糊推理系统（ANFIS）相比。
Solar activity It is vital to accurately predict solar activity, in order to decrease the plausible damage of electronic equipment in the event of a large high-intensity solar eruption. Recently, we have proposed BELFIS (Brain Emotional Learning-based Fuzzy Inference System) as a tool for the forecasting of chaotic systems. The structure of BELFIS is designed based on the neural structure of fear conditioning. The function of BELFIS is implemented by assigning adaptive networks to the components of the BELFIS structure. This paper especially focuses on performance evaluation of BELFIS as a predictor by forecasting solar cycles 16 to 24. The performance of BELFIS is compared with other computational models used for this purpose, and in particular with adaptive neuro-fuzzy inference system (ANFIS).
