. Nowadays, soft computing has been of great help in solving real-world problems and satisfying the needs in our everyday life. We require more than ever the development and implementation of models and techniques that assist in medical issues due to the recent pandemic. The aim of this work is the development and hardware implementation of a general type-2 fuzzy classifier for the pulse levels and the optimization of the general type-2 membership functions parameters using the Ant Lion Optimizer to compare results of type 1 and interval type-2 fuzzy classifiers with the patients of the Framingham database. This study additionally explains the implementation process of the general type-2 fuzzy classifier on the Jetson Nano hardware Development Board and the comparison of execution time with interval type-2, and type-1 fuzzy classifiers. This work offers a novel perspective in that the general type-2 fuzzy classifier can be implemented for embedded applications with excellent performance regarding hardware resources consumption.

。如今，软计算在解决现实世界中的问题和满足我们日常生活中的需求方面已大有帮助。我们比以往任何时候都更需要开发和实施有助于解决由于最近的大流行而引起的医疗问题的模型和技术。这项工作的目的是为脉冲电平开发通用2型模糊分类器并在硬件上实现，并使用Ant Lion Optimizer来比较1型和区间2型的结果，从而优化2型隶属函数参数。 Framingham数据库的患者有2个模糊分类器。这项研究还解释了在Jetson Nano硬件开发板上通用的2型模糊分类器的实现过程，并比较了间隔2型和1型模糊分类器的执行时间。