Power Information System Risk Assessment Method Based on Genetic Algorithms and Neural Network

Abstract:

In order to scientifically and accurately evaluate power information system, the new power information risk evaluation method based on the genetic algorithm and BP neural network is presented. The method combining the genetic algorithm and BP algorithm can be used to train the feedforward neural network , namely, first , to use the genetic algorithm to do the global training, then ,to use BP algorithm to do local precise training ,which not only overcomes the drawbacks of the traditional BP network (the training time is long, and the network is easy to fall to local extremum),but also improves the global convergence efficiency. The method was adopted to evaluate the power information system. And findings identify that the new method has distinctive convergence speed and high predicition accuracy, which provides a new concept for power information system risk assessment.

• Periodical: Applied Mechanics and Materials (Volumes 530-531)
• Pages: 429-433
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.530-531.429
• Online since: February 2014
• Authors: Heng Yang*, Ru Sen Fan, Dong Hui Xu
• Keywords: BP Neural Network (BPNN), Genetic Algorithm (GA), Power Information System, Risk Assessment

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