Prediction of Machinability characteristics of Ti6Al4V alloy using Neural Networks and Neuro-Fuzzy techniques

2018 ◽  
Vol 5 (2) ◽  
pp. 8454-8463 ◽  
Author(s):  
N. Harsha ◽  
I. Ajit Kumar ◽  
K. Sita Rama Raju ◽  
S. Rajesh
Keyword(s):  
Neural Networks ◽  
Ti6al4v Alloy ◽  
Neuro Fuzzy ◽  
Fuzzy Techniques

Neuro-Fuzzy Techniques Applied to a Ship Autopilot Design

1996 ◽  
Vol 49 (3) ◽  
pp. 410-430 ◽  
Author(s):  
Robert Sutton ◽  
Stephen D. H. Taylor ◽  
Geoffrey N. Roberts
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Royal Navy ◽  
Neuro Fuzzy ◽  
Artificial Neural ◽  
Fuzzy Techniques ◽  
Ship Autopilot

This paper is concerned with an investigation into the use of artificial neural networks in the design of fuzzy autopilots for controlling the yaw dynamics of a modern Royal Navy warship model. Results are presented to show the viability of such an approach and that effective designs can be produced.

scholarly journals Human Activities Recognition Based on Neuro-Fuzzy Finite State Machine

Technologies ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 110 ◽  
Author(s):  
Gadelhag Mohmed ◽  
Ahmad Lotfi ◽  
Amir Pourabdollah
Keyword(s):  
Neural Networks ◽  
Human Activities ◽  
Finite State Machine ◽  
Fuzzy Rule ◽  
State Machine ◽  
Machine Learning Techniques ◽  
Rule Based ◽  
Neuro Fuzzy ◽  
Finite State ◽  
Learning Capabilities

Human activity recognition and modelling comprise an area of research interest that has been tackled by many researchers. The application of different machine learning techniques including regression analysis, deep learning neural networks, and fuzzy rule-based models has already been investigated. In this paper, a novel method based on Fuzzy Finite State Machine (FFSM) integrated with the learning capabilities of Neural Networks (NNs) is proposed to represent human activities in an intelligent environment. The proposed approach, called Neuro-Fuzzy Finite State Machine (N-FFSM), is able to learn the parameters of a rule-based fuzzy system, which processes the numerical input/output data gathered from the sensors and/or human experts’ knowledge. Generating fuzzy rules that represent the transition between states leads to assigning a degree of transition from one state to another. Experimental results are presented to demonstrate the effectiveness of the proposed method. The model is tested and evaluated using a dataset collected from a real home environment. The results show the effectiveness of using this method for modelling the activities of daily living based on ambient sensory datasets. The performance of the proposed method is compared with the standard NNs and FFSM techniques.

scholarly journals Short-term and long-term thermal prediction of a walking beam furnace using neuro-fuzzy techniques

2015 ◽  
Vol 19 (2) ◽  
pp. 703-721 ◽  
Author(s):  
Hamed Banadaki ◽  
Hasan Nozari ◽  
Mahdi Shoorehdeli
Keyword(s):  
Short Term ◽  
Neuro Fuzzy ◽  
Fuzzy Techniques

Modeling research on the sorption kinetics of pentachlorophenol (PCP) to sediments based on neural networks and neuro-fuzzy systems

2007 ◽  
Vol 20 (2) ◽  
pp. 239-247 ◽  
Author(s):  
Xiao-kang Su ◽  
Guang-ming Zeng ◽  
Guo-he Huang ◽  
Jian-bing Li ◽  
Jie Liang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Fuzzy Systems ◽  
Sorption Kinetics ◽  
Neuro Fuzzy ◽  
Kinetics Of

Intelligent Biometric System Using Soft Computing Tools

2011 ◽  
pp. 259-276
Author(s):  
Anupam Shukla ◽  
Ritu Tiwari ◽  
Chandra Prakash Rathore
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Soft Computing ◽  
Fuzzy System ◽  
Person Identification ◽  
Security Applications ◽  
Neuro Fuzzy ◽  
Biometric Systems ◽  
Physical Attributes ◽  
Novel Concept

Biometric Systems verify the identity of a claimant based on the person’s physical attributes, such as voice, face or fingerprints. Its application areas include security applications, forensic work, law enforcement applications etc. This work presents a novel concept of applying Soft Computing Tools, namely Artificial Neural Networks and Neuro-Fuzzy System, for person identification using speech and facial features. The work is divided in four cases, which are Person Identification using speech biometrics, facial biometrics, fusion of speech and facial biometrics and finally fusion of optimized speech and facial biometrics.

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