Article: Soft neural network-based block chain risk estimation Journal: International Journal of Intelligent Systems Technologies and Applications (IJISTA) 2019 Vol.18 No.3 pp.257 - 270 Abstract: Financial risk refers to the uncertainty caused by the change of the economic and financial conditions. As a kind of economic phenomenon, the financial risk is objective and can not be eliminated. At present, there are still some imperfect aspects in the research of financial risk assessment. In order to achieve the purpose of comprehensive evaluation of financial risks, the paper analyses the methodology of soft computing and neural networks. The basic function of financial risk monitoring and evaluation system is to forecast the trend of financial activities and risk status, and this is also the fundamental function and objectives of the assessment system. We use BP neural network theory to establish the logistics finance risk evaluation model, using BP neural network structure and training principles to train sample data. The soft computing method is based on the factors of uncertainty and irrationality, which breaks through the limitation of traditional hard computing. There is a consistency between the fuzzy thinking principle of soft computing method and the attribute and structure of the objective world and therefore, soft computing can be used in field of financial risk assessment. Inderscience Publishers - linking academia, business and industry through research

Title: Soft neural network-based block chain risk estimation

Authors: Ganglong Duan; Wenxiu Hu; Yu Tian

Addresses: Xi'an University of Technology, Beilin District, Xi'an, Shaanxi Province, No. 5 Jinhua South Road, Xi'an, China ' Xi'an University of Technology, Beilin District, Xi'an, Shaanxi Province, No. 5 Jinhua South Road, Xi'an, China ' Xi'an University of Technology, Beilin District, Xi'an, Shaanxi Province, No. 5 Jinhua South Road, Xi'an, China

Abstract: Financial risk refers to the uncertainty caused by the change of the economic and financial conditions. As a kind of economic phenomenon, the financial risk is objective and can not be eliminated. At present, there are still some imperfect aspects in the research of financial risk assessment. In order to achieve the purpose of comprehensive evaluation of financial risks, the paper analyses the methodology of soft computing and neural networks. The basic function of financial risk monitoring and evaluation system is to forecast the trend of financial activities and risk status, and this is also the fundamental function and objectives of the assessment system. We use BP neural network theory to establish the logistics finance risk evaluation model, using BP neural network structure and training principles to train sample data. The soft computing method is based on the factors of uncertainty and irrationality, which breaks through the limitation of traditional hard computing. There is a consistency between the fuzzy thinking principle of soft computing method and the attribute and structure of the objective world and therefore, soft computing can be used in field of financial risk assessment.

Keywords: block chain; financial risk; assessment; neural network; soft computing.

DOI: 10.1504/IJISTA.2019.099343

International Journal of Intelligent Systems Technologies and Applications, 2019 Vol.18 No.3, pp.257 - 270

Received: 07 Jun 2017
Accepted: 27 Aug 2017
Published online: 29 Apr 2019 *

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Title: Soft neural network-based block chain risk estimation

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