Function approximation and neural-fuzzy approach to machining process selection

1996 ◽  
Vol 19 (1) ◽  
pp. 9-18 ◽  
Author(s):  
S.H. Huang ◽  
H.-C. Zhang ◽  
S. Sun ◽  
H.H. Li
Keyword(s):  
Function Approximation ◽  
Machining Process ◽  
Fuzzy Approach ◽  
Process Selection ◽  
Neural Fuzzy

scholarly journals Micro Machining Process Selection: An Integrated Theory

2016 ◽  
Vol 25 ◽  
pp. 862-868 ◽  
Author(s):  
Sandeep Kuriakose ◽  
Anil Varghese Mangalan ◽  
Babu Namboothiri ◽  
Amitava Ray
Keyword(s):  
Machining Process ◽  
Micro Machining ◽  
Process Selection ◽  
Integrated Theory

Rule-Based Process Selection of Hole Making Operations for Integrated Process Planning

2005 ◽  
Author(s):  
Dusan N. Sormaz ◽  
Pravin Khurana ◽  
Ajit Wadatkar
Keyword(s):  
User Interface ◽  
Manufacturing System ◽  
Selection Procedure ◽  
Machining Process ◽  
Integrated Process ◽  
Process Selection ◽  
Rule Based ◽  
Hole Making ◽  
Significant Attention ◽  
Selection Of

Process selection as a part of CAPP has captured significant attention in CAPP research. Procedures have been developed for backward and forward algorithms in process selection. Most of these procedures lack the complete integration of process selection into CAPP system. In this paper, we present the results of the development and prototype implementation for process selection module for hole making operations for integration with Math Based Manufacturing System already in use in industrial partner. We have developed architecture and implemented module for rule-based machining process selection of hole making operations. The architecture enables the interface from the Process Selection prototype to Math Based Manufacturing System (APPS). The prototype also includes the user interface for interaction with the process selection procedure. Actions for starting prototype from APPS, performing process selection steps and sending the result back to APPS have been developed and implemented.

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.

Robust neural-fuzzy method for function approximation

2009 ◽  
Vol 36 (3) ◽  
pp. 6903-6913 ◽  
Author(s):  
Horng-Lin Shieh ◽  
Ying-Kuei Yang ◽  
Po-Lun Chang ◽  
Jin-Tsong Jeng
Keyword(s):  
Function Approximation ◽  
Fuzzy Method ◽  
Neural Fuzzy
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