Power communication network reliability prediction and guarantee method and system based on deep learning

Abstract

The invention provides a power communication network reliability prediction and guarantee method and a system based on deep learning. According to the method and the system, a deep belief network anda bidirectional LSTM neural network are adopted to carry out feature extraction and prediction on state data in the network and calculated reliability index data respectively, and a network state anda corresponding reliability index in a next effective time period are predicted. Then, the predicted reliability index is evaluated; and if the standard threshold value is not met, network optimization needs to be carried out to improve the reliability of the network, and during optimization, corresponding optical cable optimization, node optimization and service level optimization are selected incombination with the predicted network basic data in the next effective time period, so that the overall reliability of the network is improved. According to the method and the system, the power communication network is optimized by combining the predicted network service state of the next time period, so that the network reliability is improved from the perspective of providing communication service stably for a long time.

Description

technical field [0001] The present invention relates to the field of power analysis, and more specifically, to a method and system for predicting and guaranteeing the reliability of power communication networks based on deep learning. Background technique [0002] The power communication network plays an extremely important role in the smart grid. Improving the reliability of the power communication network is a consistent requirement of the State Grid Corporation of China for the power communication network. By evaluating the reliability of all paths in the power communication optical fiber network, we can directly understand the distribution of network reliability. The evaluation results can be used to guide the planning, construction, operation, management and maintenance of the power communication network, which is conducive to improving the reliability of the power communication network. Reliability management level is an inevitable requirement for building a strong sma...

AI Technical Summary

Problems solved by technology

[0003] In order to solve the problem that the reliability prediction of the power communication network in the prior art is based on the accurate distribution network structure and the reliability history data of the components for many years, it can only evaluate and optimize the reliability of the current network state, but cannot predict the reliability of the future existence. Regarding the technical problem of risk prediction, the present invention provides a method for predicting and guaranteeing the reliability of power communication networks based on deep learning, the method comprising:

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