Fuzzy linguistic prediction model for sinoatrial node field potential analysis in acute hyperglycemia environment
Fuzzy linguistic prediction model for sinoatrial node field potential analysis in acute hyperglycemia environment
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DOI：
10.3233/bme-151380
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发表时间：
2015-01-01
影响因子：
1
通讯作者：
Zhang, Yanbin
中科院分区：
文献类型：
--
作者：
Feng, Yu;Cao, Hui;Zhang, Yanbin
本研究的目的是建立一个模糊语言预测模型(FLPM)来分析急性高血糖对窦房结场电位的作用时间。用微电极阵列(MEA)记录场电位。利用偏最小二乘法、支持向量机、反向传播神经网络和本文提出的方法对实验数据进行了分析。实验结果表明，该模糊语言预测模型可以用来预测高糖对窦房结电位的作用时间。与其他模型相比，该模型具有较高的预测精度。
The objective of this study is to build a fuzzy linguistic prediction model (FLPM) for analyzing the actuation duration of acute hyperglycemia to sinoatrial node field potential. The field potential was recorded using microelectrode arrays (MEA). The experimental data were analyzed using partial least squares (PLS), support vector machine (SVM), back propagation neural network (BPNN) and the proposed method. The experimental results showed that the fuzzy linguistic prediction model could be adopted for predicting the actuation duration of high glucose to the sinoatrial node field potential. Compared with the other aforementioned models, the proposed model had higher prediction accuracy.