Fuzzy neural expert system with automated extraction of fuzzy If-Then rules from a trained neural network

2002 ◽  
Author(s):  
Y. Hayashi ◽  
A. Imura
Keyword(s):  
Neural Network ◽  
Expert System ◽  
Automated Extraction ◽  
Fuzzy Neural ◽  
Trained Neural Network

Design of Credit Risk Evaluation System Based on the Fuzzy Neural Network and Expert System

2014 ◽  
Vol 543-547 ◽  
pp. 4523-4527
Author(s):  
Hong Min Zhang
Keyword(s):  
Neural Network ◽  
Risk Factors ◽  
Expert System ◽  
Credit Risk ◽  
Index System ◽  
Evaluation System ◽  
Fuzzy Neural Network ◽  
Enterprise Risk ◽  
Fuzzy Neural ◽  
Set Up

Credit risk is the main risk that Chinese commercial banks are facing. Taking into account three categories of risk factors, namely risk factors of enterprise, risk factors of commercial bank and risk factors of macroscopic economy, an index system was set up. Then, according to the index system and the characteristics of fuzzy neural network and expert system, a credit risk rating system based on fuzzy neural network and expert system was proposed.

Advanced Process Control Expert System of CVD Membrane Thickness Based on Neural Network

2006 ◽  
Vol 505-507 ◽  
pp. 313-318 ◽  
Author(s):  
Ming Chang ◽  
Jen Cheng Chen ◽  
Jui Wen Chang ◽  
Jia Sheng Heh
Keyword(s):  
Neural Network ◽  
Expert System ◽  
Process Control ◽  
Process Parameters ◽  
Chemical Vapor ◽  
Thin Film Deposition ◽  
Film Deposition ◽  
Membrane Thickness ◽  
On Line ◽  
Trained Neural Network

A membrane thickness process control expert system of chemical vapor deposition (CVD) based on neural network is presented. In general, there are many factors would influence the membrane quality. Most of them can be adjusted by changing the recipe, which are the process parameters of the working machines. Finding out a suitable and steady recipe and on-line real-time controlling the recipe is the target that process engineers devote to. Generally speaking, the recipe adjustment is based on the accumulation of experiences or learning from the try and error results. However, the process of thin film deposition is a very complicate and nonlinear system. It is very difficult to find out the relationships between the variation of process parameters and membrane quality. Therefore, a system was developed to simulate the CVD’s process using a technique of neural network. An expert system was then set up by extracting out the regular rule between process input and output from the trained neural network, which would provide references to engineers for the need of on-line recipe adjustment.

Fault Diagnosis Expert System for Special Electronic Equipment Based on the Fuzzy Neural Network

2012 ◽  
Vol 241-244 ◽  
pp. 401-404
Author(s):  
Xue Zhong Yin ◽  
Jie Gui Wang
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Expert System ◽  
Fuzzy Neural Network ◽  
Electronic System ◽  
Electronic Equipment ◽  
Diagnostic Model ◽  
Model Based ◽  
Proposed Model ◽  
Fuzzy Neural

In order to improve the efficiency and reliability of fault diagnosis for the special electronic equipment, an intelligent fault diagnostic model based on Fuzzy Neural Network (FNN) is proposed. Firstly, the fault diagnosis model based on the FNN Expert System (ES) is built. Secondly, the fault diagnosis expert system of the special electronic equipment based on this model is introduced. Finally, experiments show that the proposed model is correct and the FD system is effective. Moreover, the given method provides a new way of fault diagnosis for other modern electronic system.

scholarly journals Synthesis of an Expert System for Assessing the Security of Computer Networks Based on a Fuzzy Neural Network

2020 ◽  
Vol 9 (7) ◽  
pp. 935-939
Keyword(s):  
Neural Network ◽  
Expert System ◽  
Computer Networks ◽  
Fuzzy Neural Network ◽  
Computer Systems ◽  
The United States ◽  
Fuzzy Neural Networks ◽  
Practical Significance ◽  
United States Department ◽  
Fuzzy Neural

The aim of the article is to substantiate the principles of synthesis of an expert system for assessing the security of computer networks based on a fuzzy neural network, and this is an urgent scientific and technical task. Requirements for the operative security assessment of computer networks for data protection are analyzed. It was shown that data security should be provided by the network administrator or persons who need to use special decision support systems in assessing the security of computer networks. To solve this problem, factors that characterize the security of electronic systems, including computer systems, have been identified; the use of fuzzy neural networks is proposed as a mathematical apparatus for constructing an expert system; a technique for the synthesis of a fuzzy neural network for assessing the security of computer networks has been developed; an appropriate fuzzy neural network has been created and tested for adequacy; the prospects of the proposed methodology for creating an expert system for assessing the security of computer systems have been established. The scientific and practical significance of developing such a system lies in the fact that a fuzzy neural network is configured on a specific object in order to quickly determine one of the seven levels of security of computer networks that are used in the United States Department of Defense.

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