Application of T-S fuzzy neural network in safety risk assessment of textile and apparel

2011 ◽  
Author(s):  
Shuhui Pang ◽  
Yuan Zhou ◽  
Xuemei Ding ◽  
Xiongying Wu
Keyword(s):  
Neural Network ◽  
Risk Assessment ◽  
Fuzzy Neural Network ◽  
Safety Risk ◽  
Textile And Apparel ◽  
Fuzzy Neural

The Study and Realization of Grading Modeling Risk Assessment for Buried Gas Pipeline

2014 ◽  
Vol 945-949 ◽  
pp. 2944-2953
Author(s):  
Long Jiang Li ◽  
Jin Yu An ◽  
Lan Zhou
Keyword(s):  
Neural Network ◽  
Risk Assessment ◽  
Fuzzy Neural Network ◽  
Fault Tree Analysis ◽  
Gas Pipeline ◽  
Factors Affecting ◽  
Fuzzy Neural ◽  
Neural Network Theory ◽  
Buried Gas Pipeline ◽  
Network Risk

According to the risk assessment conducted on buried gas pipelines,it is found that the number of factors affecting pipeline failure is more than 130 and that it could not reach the requirement by using a model to calculate or evaluate.On the base of the traditional buried gas pipeline fault tree analysis, this paper puts forward a thought of the grading modeling risk assessment,adopting the compensation fuzzy neural network theory . The fault trees minimal cut sets grading modeling helps to establish the mathematical model of compensation fuzzy neural network risk assessment, deduce the model error transformation formula, revise the assessment errors ,and solve the problem of risk assessment of the large buried gas pipelineswhich needs to consider many assessment factors. The practical study demonstrates that the assessment results are objective and the assessment errors are small.

scholarly journals Research on Supply Chain Financial Risk Assessment Based on Blockchain and Fuzzy Neural Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yijie Wang
Keyword(s):  
Neural Network ◽  
Risk Assessment ◽  
Supply Chain ◽  
Credit Risk ◽  
Fuzzy Neural Network ◽  
Financial System ◽  
Fuzzy Neural Networks ◽  
Machine Learning Algorithms ◽  
Supply Chain Finance ◽  
Fuzzy Neural

With the development of supply chain finance, the credit risk of small- and medium-sized financing enterprises from the perspective of supply chain finance has arisen. Risk management is one of the key tasks of the credit business of banks and other financial institutions, which runs through all aspects of the credit business before, during, and after the loan. This article combines blockchain and fuzzy neural network algorithms to study the credit risk of SME financing from the perspective of supply chain finance. This article builds a supply chain financial system through blockchain technology and integrates supply chain financial information into blocks. The fuzzy neural network algorithm is used for financial data processing and risk assessment, effectively solving and improving the risk processing level of the supply chain. Through further simulation, the application effect of blockchain and machine learning algorithms in the supply chain financial system was verified.

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