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Individual prediction of the hypertensive patient condition based on computational intelligence

机译:基于计算智能的高血压患者病情个体预测

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The problem of development of information technology for individual health prediction of hypertensive patient is solved. The method of neuro-fuzzy networks synthesis based on parallel computing is proposed. It uses the stochastic approach for finding the values of adjustable parameters of neuro-fuzzy networks. It consists of the distribution of the most resource-intensive stages on the nodes of parallel computing system that reduces the time of calculation of synthesized neuro-model's parameters. The software implementing the proposed parallel method is developed. The experiments on the solution of practical problem of individual health prediction of hypertensive patient are conducted.
机译:解决了高血压患者个体健康预测信息技术的发展问题。提出了一种基于并行计算的神经模糊网络综合方法。它使用随机方法来查找神经模糊网络的可调参数值。它由并行计算系统的节点上最耗费资源的阶段的分布组成,从而减少了合成神经模型参数的计算时间。开发了实现所提出的并行方法的软件。为解决高血压患者个人健康预测的实际问题,进行了实验。

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