Interval type-2 fuzzy logic gravitational search algorithm for the optimization of modular neural networks in echocardiogram recognition

被引：0
|
作者：
Gonzalez, Beatriz [1 ]
Melin, Patricia [1 ]
Valdez, Fevrier [1 ]
Prado-Arechiga, German [2 ]
机构：
[1] Tijuana Inst Technol, Tijuana, Mexico
[2] Cardiodiagnostico, Paseo Heroes 2507, Zona Rio, Tijuana, Mexico
来源：
PROCEEDINGS OF 2016 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI) | 2016年
关键词：
echocardiography images; GSA; MNN; PARTICLE SWARM OPTIMIZATION; GENETIC ALGORITHMS; GSA;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Research in echocardiogram imaging it's very important because it allows assessing both anatomy and cardiac function, help diagnose various diseases. In this paper to find the optimal architecture of a MNN, where means finding the number of layers and nodes. In this case the Type-2 fuzzy logic gravitational search algorithm is used for optimizing the MNN for pattern recognition in echocardiogram imaging.
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页数：7
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