• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Intelligence Science >Recurrent Self-evolving Takagi-Sugeno-Kan Fuzzy Neural Network (RST-FNN) Based Type-2 Diabetic Modeling
【24h】

Recurrent Self-evolving Takagi-Sugeno-Kan Fuzzy Neural Network (RST-FNN) Based Type-2 Diabetic Modeling

机译：经常性的自我发展Tapagi-Sugeno-KAN模糊神经网络（RST-FNN）Type-2糖尿病型造型

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Diabetes mellitus affected an estimated 463 million people in the year 2019. The number of diabetic patients is projected to increase to an alarming figure of 700 million by the year 2045, out of which 90-95% of them are expected to be type 2 diabetes mellitus (T2DM) patients. The research presented an alternative way of state-of-the-art insulin therapy using manual insulin infusion. The T2DM model that simulates the body reaction of a T2DM patient has been developed using real human clinical data that uses insulin pump therapy. The proposed system uses a closed-loop control together with fuzzy gain scheduling and recurrent self-evolving Takagi-Sugeno-Kang fuzzy neural network (RST-FNN). Such a system will help the patient remove the need for manual insulin infusion. This proposed system will record the blood glucose level and predict the next iteration's blood glucose level. The change in blood glucose level will help detect the food intake (carbohydrates) with reference to the gain scheduler and the controller will communicate with the insulin pump to infuse the corresponding amount of insulin.
机译：2019年糖尿病患者估计影响了4.63亿人口。预计糖尿病患者的数量将增加到2045年的7亿令人令人担忧的数字，其中90-95％预计将是2型糖尿病mellitus（T2DM）患者。该研究呈现了使用手动胰岛素输注的最先进的胰岛素治疗方法。使用使用胰岛素泵疗法的真正的人类临床数据，开发了模拟T2DM患者体内反应的T2DM模型。所提出的系统使用闭环控制以及模糊增益调度和经常性的自我发展Takagi-sugeno-kang模糊神经网络（RST-FNN）。这种系统将有助于患者去除手动胰岛素输注的需要。该提出的系统将记录血糖水平并预测下一个迭代的血糖水平。血糖水平的变化将有助于参考增益调度器检测食物摄入（碳水化合物），并且控制器将与胰岛素泵通信以输注相应的胰岛素。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号