scholarly journals INTELLIGENT VEHICLE PARKING USING FUZZY-NEURAL NETWORKS

2013 ◽  
pp. 14-18
Author(s):  
Subhrajit Pradhan ◽  
Srikant Patnaik ◽  
Sukanta Kumar Tulo
Keyword(s):  
Neural Networks ◽  
Fuzzy Controller ◽  
Fuzzy Neural Networks ◽  
Intelligent Vehicle ◽  
Practical Implementation ◽  
Positioning Error ◽  
Neural Controller ◽  
Different Types ◽  
Fuzzy Neural ◽  
Refined Version

This paper analyzes the performance and practical implementation of fuzzy-neural networks for the autonomous motion of mobile robots. The designed fuzzy-neural controller is a refined version of a conventional fuzzy controller, and was trained to optimize a given cost function minimizing positioning error. It was found that the mobile robot with fuzzyneural controller presents good positioning and tracking performance for different types of desired trajectories. It was verified by computer simulation as well as experimentally using a laboratory-scale car-like robot model.

scholarly journals Types of Arcs in Complement of a Fuzzy Graph

2011 ◽  
Vol 10 (2) ◽  
pp. 75-81
Author(s):  
K.R. Sandeep Narayan ◽  
M.S. Sunitha
Keyword(s):  
Neural Networks ◽  
Fuzzy Neural Networks ◽  
Fuzzy Graph ◽  
Fuzzy Graphs ◽  
Different Types ◽  
Fuzzy Neural

Connectivity has important role in the area of applications of fuzzy graphs such as fuzzy neural networks and clustering. In this paper different types of arcs such as α, β, δ and fuzzy bonds are analyzed in a fuzzy graph G and its complement.

scholarly journals FUZZY NEURAL NETWORKS IN INTELLIGENT MANUFACTURING SYSTEMS

2014 ◽  
pp. 96-100
Author(s):  
Galina Setlak
Keyword(s):  
Neural Networks ◽  
Development Strategy ◽  
Manufacturing Systems ◽  
Quantitative Information ◽  
Intelligent Manufacturing ◽  
Fuzzy Neural Networks ◽  
Practical Implementation ◽  
Fuzzy Neural ◽  
Decision Making Processes ◽  
Product Development Strategy

This paper presents fuzzy neural networks, which are an expansion of classical neural networks. These networks can formally represent and process both the qualitative (linguistic) and quantitative information, which usually describe a complex, multidimensional systems or decision making processes. The second part presents the results of tests and a practical implementation of applications for decision support systems based on fuzzy neural networks used for strategic management and determination of product development strategy.

Modeling of Self-Induced Vibrations that Occur During the Machining Process of Casting Patterns with the Use of The Fuzzy-Neural Networks Method

2013 ◽  
Vol 58 (3) ◽  
pp. 871-875
Author(s):  
A. Herberg
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Network Structure ◽  
Fuzzy Systems ◽  
Fuzzy Neural Networks ◽  
Cnc Machining ◽  
Machining Process ◽  
Modeling Process ◽  
Fuzzy Neural ◽  
Takagi Sugeno

Abstract This article outlines a methodology of modeling self-induced vibrations that occur in the course of machining of metal objects, i.e. when shaping casting patterns on CNC machining centers. The modeling process presented here is based on an algorithm that makes use of local model fuzzy-neural networks. The algorithm falls back on the advantages of fuzzy systems with Takagi-Sugeno-Kanga (TSK) consequences and neural networks with auxiliary modules that help optimize and shorten the time needed to identify the best possible network structure. The modeling of self-induced vibrations allows analyzing how the vibrations come into being. This in turn makes it possible to develop effective ways of eliminating these vibrations and, ultimately, designing a practical control system that would dispose of the vibrations altogether.

Hotbox level detection of railway vehicle using fuzzy neural networks

2013 ◽  
Vol 33 (9) ◽  
pp. 2566-2569 ◽  
Author(s):  
Zhuanling CUI ◽  
Guoning LI ◽  
Sen LIN
Keyword(s):  
Neural Networks ◽  
Fuzzy Neural Networks ◽  
Railway Vehicle ◽  
Fuzzy Neural

scholarly journals Affine Memory Control for Synchronization of Delayed Fuzzy Neural Networks

IEEE Access ◽  
2020 ◽  
pp. 1-1
Author(s):  
Wookyong Kwon ◽  
Yongsik Jin ◽  
Dongyeop Kang ◽  
Sangmoon Lee
Keyword(s):  
Neural Networks ◽  
Fuzzy Neural Networks ◽  
Fuzzy Neural ◽  
Memory Control
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