Stress prediction model of tower-line system in landslide area based on IHPO-BP neural network
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1.Collage of Electrical Engineer &2.New Energy, China Three Gorges University;3.amp;4.State Grid Lanzhou Electric Power Supply Company

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National natural science foundation of China

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    Abstract:

    In order to solve the problem that the transmission tower-line system in landslide area is prone to rod failure under the action of slope deformation and wind load, a stress prediction model of tower-line system in landslide area based on IHPO-BP neural network is proposed. Firstly, the improved Circle chaotic mapping, nonlinear strategy of balance factor and Levy flight are used to optimize the hunter-prey optimization algorithm, and then the improved hunter-prey optimization algorithm is used to optimize the weights and thresholds of BP neural network, and the stress prediction model of tower-line system in landslide area is obtained. The wind direction angle, wind speed and displacement of tower leg support are used as model inputs, and the maximum stress of tower-line system members is used as output. The prediction results show that the IHPO-BP model proposed in this paper has high convergence speed and prediction accuracy. Compared with the HPO-BP model, the average absolute error decreases by 71.7%, the root mean square error decreases by 76.6% and the average relative error decreases by 71.8%.

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History
  • Received:May 24,2023
  • Revised:August 07,2023
  • Adopted:August 10,2023
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