电池2024，Vol.54Issue(6)：772-776,5.DOI:10.19535/j.1001-1579.2024.06.003
燃料电池预测模型输出结果统计分析
Statistical analysis of the output results of fuel cell prediction model
摘要
Abstract
Due to the randomness,fuel cell lifetime prediction models based on neural network algorithms have uncertainty in their output results,meaning that the output is different with each prediction.To address this issue,a fuel cell lifetime prediction model based on the long short-term memory(LSTM)neural network algorithm is established.This model is run multiple times on the experimental sample data,statistical methods are used to analyze the statistical characteristics of the distribution of output results.It is found that the output results of the LSTM neural network-based lifetime prediction model follow a normal distribution pattern.Based on this conclusion,the average of multiple results can be used as the output of the fuel cell lifetime prediction model,thereby improving the prediction accuracy and stability of the output results.关键词
燃料电池/寿命预测模型/正态分布检验/长短时记忆(LSTM)神经网络/统计特性Key words
fuel cell/lifetime prediction model/normal distribution test/long short-term memory(LSTM)neural network/statistical characterization分类
信息技术与安全科学引用本文复制引用
鲁源博,侯永平,焦道宽,王要娟..燃料电池预测模型输出结果统计分析[J].电池,2024,54(6):772-776,5.基金项目
国家重点研发计划重点专项(2023YFE0109200) （2023YFE0109200）
