Ward Em, Martin Terry
Biomedical and Electrical Engineering, University of Arkansas, Fayetteville 72701, USA.
J Med Syst. 2006 Jun;30(3):187-203. doi: 10.1007/s10916-005-7983-2.
We present a detailed glucose regulation model using fuzzy inference system (FIS) descriptions of hormonal control action and the familiar Michaelis-Menten (M-M) kinetic description for glucose transport. The fuzzy M-M model is compared and contrasted with a well-known comprehensive glucose model. The two models give similar results for glucose response, endogenous glucose production, and total uptake. The fuzzy M-M model features a renal subsystem that provides 25% of the endogenous glucose production. The work demonstrates the successful application of fuzzy logic and fuzzy inference to biological modelling. The flexibility of fuzzy inference, a linguistic description technique, permits conceptually simple statements about nonlinear processes.
我们提出了一个详细的葡萄糖调节模型,该模型使用模糊推理系统(FIS)对激素控制作用进行描述,并采用大家熟知的米氏(M-M)动力学描述来描述葡萄糖转运。将模糊M-M模型与一个著名的综合葡萄糖模型进行了比较和对比。这两个模型在葡萄糖反应、内源性葡萄糖生成和总摄取方面给出了相似的结果。模糊M-M模型具有一个肾脏子系统,该子系统提供25%的内源性葡萄糖生成。这项工作证明了模糊逻辑和模糊推理在生物建模中的成功应用。模糊推理作为一种语言描述技术,其灵活性允许对非线性过程进行概念上简单的表述。