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Risk Assessment Method of Agricultural Management Investment Based on Genetic Neural Network
Author(s) -
JingJing Zhao
Publication year - 2022
Publication title -
security and communication networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.446
H-Index - 43
eISSN - 1939-0114
pISSN - 1939-0122
DOI - 10.1155/2022/2373363
Subject(s) - investment (military) , agriculture , risk analysis (engineering) , risk assessment , genetic algorithm , risk management , business , financial risk , computer science , investment strategy , artificial neural network , finance , artificial intelligence , computer security , machine learning , ecology , politics , political science , market liquidity , law , biology
At present, the economy has entered the new normal. In the environment of economic slowdown, agricultural operation and investment risk management is of great significance in investment activities. In order to avoid the related risks of the agricultural operation and investment, improve the stability of agricultural operation and investment risk assessment, and ensure the effect of the agricultural operation and investment risk assessment, an agricultural operation and investment risk assessment method based on genetic neural network is proposed. This method fully considers the global optimization capability of the genetic algorithm and optimizes the weights and thresholds of the BP neural network. According to the construction principle of the index system, from the perspective of systemic risk and nonsystematic risk, a risk assessment index system for agricultural business investment has been established. Based on the establishment of risk evaluation index system, using the genetic neural network method, the agricultural operation investment risk evaluation model is established to realize the agricultural operation investment risk evaluation. The experimental results show that the proposed method has a good effect on the risk assessment of the agricultural operation and investment and can effectively improve the stability of the risk assessment of agricultural operation and investment.

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