基于模糊集与神经网络的亚健康诊断

Diagnosis of the quasi-health state based on the fuzzy sets and neural networks

利用人工神经网络与模糊集的理论和方法提出了诊断亚健康状态的一种分类器模型.通过选取影响亚健康较为重要的几个因素作为输入矢量,利用感知器模型确定身体健康状态,由此给出治疗建议.将神经网络应用于亚健康诊治,给人们诊断亚健康提供了一种简便有效的方法,缓解了临床医学检查中对亚健康难以发现和评判的难题.

This paper, based on the theory and method of artificial nerve networks and fuzzy sets, puts forward a classifier model used for diagnosing the quasi-heath state. By selecting several relatively important factors affecting quasi-health as input vector and by using perception model, the health state of human body can be determined and thus the corresponding diagnosis and treatment will be found. The application of neural networks to the diagnosis of the quasi-health state provides people with a simple but effective method to diagnose quasi-health state, and it reduces the difficulty in identification and assessment of the quasi-health state in clinical examination.