Intelligent system for control of a stepping motor drive using a hybrid neuro-fuzzy approach

2002 ◽  
Author(s):  
Melin ◽  
Castillo
Keyword(s):  
Intelligent System ◽  
Motor Drive ◽  
Fuzzy Approach ◽  
Stepping Motor ◽  
Neuro Fuzzy

Agility of Supply Chain Management Solution Using Neural-Fuzzy Approach

2019 ◽  
Vol 16 (10) ◽  
pp. 4143-4148 ◽  
Author(s):  
Avinash Sharma ◽  
Aarti M. Karande ◽  
Dhananjay R. Kalbande
Keyword(s):  
Supply Chain ◽  
Business Process ◽  
Intelligent System ◽  
Business Environment ◽  
Rule Base ◽  
Fuzzy Approach ◽  
Computing Technique ◽  
Neuro Fuzzy ◽  
Soft Computing Technique ◽  
Unpredictable Environment

Enterprise solution is the architecture of collecting and processing business information. Business process agility affects process-based applications works as per changing business environment. This paper helps to understand different changing environment of business process in the supply chain domain. Changes depend on organizational policy; hence it can be incomplete or uncertain. To manage this unpredictable environment, a soft computing technique is used for constructing intelligent system. This paper shows use of Neuro-fuzzy approach to monitor agile behavior of the business process. Neural network phase is used for finding business process and parameter criticality. Fuzzy logic rule base phase calculates process agility based on the relation between process and it’s affecting parameter. Developed tool, shows that business architecture level is more prone to changes as compared to other architectural levels from the enterprise solution.

Intelligent control of a stepping motor drive using a hybrid neuro-fuzzy ANFIS approach

2003 ◽  
Vol 3 (3) ◽  
pp. 209-219 ◽  
Author(s):  
Leocundo Aguilar ◽  
Patricia Melin ◽  
Oscar Castillo
Keyword(s):  
Intelligent Control ◽  
Motor Drive ◽  
Stepping Motor ◽  
Neuro Fuzzy

scholarly journals Weather Modeling Using Data-Driven Adaptive Rough-Neuro-Fuzzy Approach

2017 ◽  
Vol 12 (2) ◽  
pp. 429-435
Author(s):  
M. Sudha
Keyword(s):  
Intelligent Systems ◽  
Prediction Accuracy ◽  
Intelligent System ◽  
Data Driven ◽  
Fuzzy Approach ◽  
Neuro Fuzzy ◽  
Proposed Model ◽  
Hybrid Data ◽  
Weather Modeling ◽  
Using Data

Recently, hybrid data-driven models have become appropriate predictive patterns in various hydrological forecast scenarios. Especially, meteorology has witnessed that there is a need for a much better approach to handle weather-related parameters intelligently. To handle this challenging issue, this research intends to apply the fuzzy and ANN theories for developing hybridized adaptive rough-neuro-fuzzy intelligent system. . Assimilating the features of ANN and FIS has attracted the rising attention of researchers due to the growing requisite of adaptive intelligent systems to solve the real world requirements. The proposed model is capable of handling soft rule boundaries and linguistic variables to improve the prediction accuracy. The adaptive rough-neuro-fuzzy approach attained an enhanced prediction accuracy of 95.49 % and outperformed the existing techniques.

A Neuro-Fuzzy Controller for Doubly FED Asynchronous Motor Drive

2010 ◽  
Vol 4 (1) ◽  
pp. 8-15
Author(s):  
Azeddine Chaiba ◽  
◽  
Rachid Abdessemed ◽  
M. Lokmen Bendaas ◽  
◽  
...  
Keyword(s):  
Fuzzy Controller ◽  
Asynchronous Motor ◽  
Motor Drive ◽  
Neuro Fuzzy ◽  
Doubly Fed
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