Neurofuzzy inference system for diagnosis of malaria

Aayush Rastogi, N. Gupta, P. Tyagi
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引用次数: 2

Abstract

In this paper, a structure of adaptive system is proposed with the help of Neurofuzzy System (NFS) for diagnosis of Malaria. Investigation of malaria using Neurofuzzy system has been used for decision making ability based on predefined rules and learning by the backpropagation algorithm. Mapping Network in backpropagation algorithm is applied to minimize the errors in the output. Investigation of malaria by the proposed system is illustrated and good performance is achieved with maximum instant error of 0.06144.
疟疾诊断的神经模糊推理系统
本文提出了一种基于神经模糊系统(NFS)的疟疾诊断自适应系统结构。利用神经模糊系统进行疟疾研究,具有基于预定义规则和反向传播算法学习的决策能力。采用反向传播算法中的映射网络,使输出误差最小。应用该系统对疟疾进行了研究,取得了良好的效果,最大瞬时误差为0.06144。
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