A comparative study on fuzzy Mamdani-Sugeno-Tsukamoto for the childhood tuberculosis diagnosis
A comparative study on fuzzy Mamdani-Sugeno-Tsukamoto for the childhood tuberculosis diagnosis
复制标题
模糊Mamdani-Sugeno-Tsukamoto儿童结核病诊断的比较研究
DOI：
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发表时间：
2016
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通讯作者：
S. Fauziati
中科院分区：
文献类型：
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作者：
Wahyuni Eka Sari;O. Wahyunggoro;S. Fauziati
世界卫生组织(世卫组织)估计，每年约有8万儿童死于儿童结核病。考虑到在儿科患者中确定诊断的困难，这种疾病需要适当的治疗。儿童不能产生痰成为困难之一。根据痰中的结核分枝杆菌，痰被用来诊断一个人患有结核病。本文将Mamdani、Tsukamoto和Sugeno-type模糊推理系统应用于结核病辅助诊断。这三种方法的不同技术旨在确定最适合此类诊断的方法。结果表明，在三种模糊推理系统中，Sugeno模型是最好的模型。Sugeno-type FIS的准确率高于Mamdani和Tsukamoto，准确率为93%，相当于180名患者中的13名患者的诊断准确率。在这里，Mamdani型FIS的诊断准确率为89%，相当于...
World Health Organization (WHO) estimated that approximately 80 thousand children died every year in view of Childhood Tuberculosis. The disease needs an appropriate treatment considering the difficulties in establishing a diagnosis in pediatric patients. The incapability of children to produce sputum becomes one of the difficulties. Sputum is used to diagnose a person suffering from tuberculosis, based on Mycobacterium tuberculosis in sputum. In this paper, Mamdani, Tsukamoto and Sugeno-types Fuzzy Inference System are applied to assist the tuberculosis diagnosis. The different technique in these three methods is aimed to determine the most appropriate method for such diagnosis. The results show that, of the three types of Fuzzy Inference System, the best model is Sugeno model. Sugeno-type FIS has a better accuracy compared to both Mamdani and Tsukamoto ones at 93%, equivalent to a fault diagnosis in 13 of 180 patients. Here, Mamdani-type FIS is provided the diagnostic accuracy of 89%, equivalent to the ...