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首页> 外文会议>International Forum on Electrical Engineering and Automation >Application of GA-LSTM model in cable Joint temperature prediction
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Application of GA-LSTM model in cable Joint temperature prediction

机译：GA-LSTM模型在电缆接头温度预测中的应用

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The safety of the power cable running system directly affects the safety and reliability of the power supply. Due to most of the cable fault occurred in the cable joint parts, it's necessary to improve the security of power cable running system. This paper shows an algorithm based on GA - LSTM to predict the cable joint temperature. That's genetic algorithm optimizes the network structure of LSTM model, gets the best LSTM prediction model, and uses the collected data set of cable joint temperature on the established model for training. The training results show that the GA-LSTM algorithm can get a more accurate temperature prediction value and less error than the LSTM network under the condition of large samples, and it has a good application for the prediction of cable temperature.
机译：电力电缆运行系统的安全性直接影响电源的安全性和可靠性。由于电缆接头部件中大部分电缆故障发生，有必要提高电力电缆运行系统的安全性。本文介绍了一种基于GA - LSTM的算法，以预测电缆接头温度。该遗传算法优化了LSTM模型的网络结构，获得了最佳的LSTM预测模型，并使用所建立的培训模型上的电缆接头温度的收集数据集。培训结果表明，在大型样品的条件下，GA-LSTM算法可以获得比LSTM网络更精确的温度预测值和更小的误差，并且它具有良好的应用来预测电缆温度。

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