Application of Neural-Fuzzy System in Prediction of Methane Hazard

2017 ◽  
pp. 151-160 ◽  
Author(s):  
Dariusz Felka ◽  
Jarosław Brodny
Keyword(s):  
Fuzzy System ◽  
Neural Fuzzy

Functional-type single-input-rule-modules connected neural fuzzy system for wind speed prediction

2017 ◽  
Vol 4 (4) ◽  
pp. 751-762 ◽  
Author(s):  
Chengdong Li ◽  
Li Wang ◽  
Guiqing Zhang ◽  
Huidong Wang ◽  
Fang Shang
Keyword(s):  
Wind Speed ◽  
Fuzzy System ◽  
Functional Type ◽  
Wind Speed Prediction ◽  
Speed Prediction ◽  
Single Input ◽  
Neural Fuzzy

Application of Hybrid Neural Fuzzy System (ANFIS) in Food Processing and Technology

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

scholarly journals A self-constructing compensatory neural fuzzy system and its applications

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

scholarly journals An integrated inverse adaptive neural fuzzy system with Monte-Carlo sampling method for operational risk management

2018 ◽  
Vol 98 ◽  
pp. 11-26 ◽  
Author(s):  
Alejandro Peña ◽  
Isis Bonet ◽  
Christian Lochmuller ◽  
Francisco Chiclana ◽  
Mario Góngora
Keyword(s):  
Risk Management ◽  
Monte Carlo ◽  
Fuzzy System ◽  
Sampling Method ◽  
Operational Risk ◽  
Monte Carlo Sampling ◽  
Operational Risk Management ◽  
Neural Fuzzy

A Novel Neural Fuzzy Approach for Diagnosis of Potassium Disturbances

2013 ◽  
pp. 208-218
Author(s):  
Mashhour Bani Amer ◽  
Mohammad Amawi ◽  
Hasan El-Khatib
Keyword(s):  
Expert System ◽  
Fuzzy System ◽  
Critical Time ◽  
Diagnostic System ◽  
Accurate Diagnosis ◽  
Fuzzy Expert System ◽  
Fuzzy Approach ◽  
Neuro Fuzzy ◽  
Precise Diagnosis ◽  
Neural Fuzzy

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.

Hydraulic Torque Converter’s Performance Analysis Based on Neural-Fuzzy System

2011 ◽  
Vol 71-78 ◽  
pp. 2002-2005
Author(s):  
Guo Fu Tian ◽  
Ke Qiang Feng ◽  
Shu Hui Sun
Keyword(s):  
Data Processing ◽  
Fuzzy System ◽  
Original Data ◽  
Torque Converter ◽  
Data Handling ◽  
Experiment Data ◽  
Processing Ability ◽  
Hydraulic Torque Converter ◽  
Experiment Analysis ◽  
Neural Fuzzy

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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