A neural-fuzzy system for the protein folding problem

Author(s):  
W.C. Daugherity
2017 ◽  
Vol 4 (4) ◽  
pp. 751-762 ◽  
Author(s):  
Chengdong Li ◽  
Li Wang ◽  
Guiqing Zhang ◽  
Huidong Wang ◽  
Fang Shang

2016 ◽  
Vol 8 (3) ◽  
pp. 351-366 ◽  
Author(s):  
Majdi Al-Mahasneh ◽  
Mohannad Aljarrah ◽  
Taha Rababah ◽  
Muhammad Alu’datt

2005 ◽  
Vol 42 (3-4) ◽  
pp. 339-351 ◽  
Author(s):  
Cheng-Jian Lin ◽  
Cheng-Hung Chen
Keyword(s):  

2018 ◽  
Vol 98 ◽  
pp. 11-26 ◽  
Author(s):  
Alejandro Peña ◽  
Isis Bonet ◽  
Christian Lochmuller ◽  
Francisco Chiclana ◽  
Mario Góngora

Author(s):  
Mashhour Bani Amer ◽  
Mohammad Amawi ◽  
Hasan El-Khatib

In this paper, a neural fuzzy system for the diagnosis of potassium disturbances is presented. This paper develops an adaptive neuro-fuzzy expert system that can provide accurate diagnosis of potassium disturbances. The proposed diagnostic approach has many attractive features. First, it provides an efficient tool for diagnosis of K+ disturbances and aids clinicians, especially the non-expert ones, in providing fast and accurate diagnosis of K+ disturbances in critical time. Second, it significantly reduces the time needed to accomplish precise diagnosis of K+ disturbances and thus enhances the healthcare standards. Third, it is capable of diagnosing the different types of potassium disturbances using a hybrid neural fuzzy approach. Finally, it has good accuracy (higher than 87%), specificity (100%), and average sensitivity (83%). The performance of the proposed diagnostic system was experimentally evaluated and the achieved results confirmed that the proposed system is efficient and accurate in diagnosing K+ disturbances.


2011 ◽  
Vol 71-78 ◽  
pp. 2002-2005
Author(s):  
Guo Fu Tian ◽  
Ke Qiang Feng ◽  
Shu Hui Sun

Aimed at the need of data processing and analysis in the performance experiment of hydraulic torque converter, we put forward a way of experiment data analysis using neural-fuzzy system. It can reduce manual participation, improve the data processing ability, accelerate computing velocity and realize data handling automation. We can judge product’s performance by this method. The use in experiment data indicates that it can express the relation of original data nicely. The identifying accuracy of data is good. It can satisfy the request of experiment analysis and the analytical conclusion is accurate too.


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