Hybrid model for medical diagnosis using Neutrosophic Cognitive Maps with Genetic Algorithms

被引：0
|
作者：
Gaurav [1 ]
Kumar, Megha [1 ]
Bhutani, Kanika [1 ]
Aggarwal, Swati [2 ]
机构：
[1] ITM Univ, CSE&IT Dept, Gurgaon, India
[2] NSIT Dwarka, COE, New Delhi, India
来源：
2015 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2015) | 2015年
关键词：
Neutrosophic cognitive maps; genetic algorithm; medical decision support system; FUZZY; INCONSISTENCY; PREDICTION;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper presents a combination of two soft computing techniques: Neutrosophic cognitive maps and Genetic algorithm for modeling of medical disease diagnosis. Earlier, medical decision support system was proposed by many researchers where cognitive maps along with genetic algorithm were experimented. The hybrid model of fuzzy cognitive maps with genetic algorithm was implemented to handle situations where decisions are not clearly distinct. In real world situation data is not always consistent so, authors proposed a new hybrid model of Neutrosophic Cognitive Maps with Genetic Algorithms to handle indeterminacy. The proposed model will provide distinct diagnosis of disease in medical decision support system.
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页数：7
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