计算机应用与软件2025，Vol.42Issue(5)：25-29,61,6.DOI:10.3969/j.issn.1000-386x.2025.05.004
基于TCN模型的软件系统老化预测框架
SOFTWARE SYSTEM AGING PREDICTION FRAMEWORK BASED ON TEMPORAL CONVOLUTIONAL NETWORK
摘要
Abstract
With the expansion of software scale expansion and logic complexity,software aging characteristics are more hidden,and the aging parameters timing signal is more complex.In view of the high requirements of the time series prediction method for sequence stationarity and the problems of slow convergence speed and easy trapping in local extremum of the BP neural network,a model of aging prediction software framework is proposed based on time domain convolution network(TCN).The available memory data was collected as the input of the framework and predicted by TCN model.The efficiency of the model was evaluated by checking the average error between the predicted output memory and the actual memory.Compared with ARIMA model and RNN(LSTM)model,TCN model has lower requirements on time series stability and better adaptability,and has no problems of gradient explosion or disappearance,and has the best prediction effect on acquired aging data.关键词
软件老化/时域卷积网络/老化预测框架/预测误差/差分自回归滑动平均模型/长短时记忆模型Key words
Software aging/Temporal convolutional network(TCN)/Aging prediction framework/Prediction error/Autoregressive integrated moving average(ARIMA)/Long short-term memory(LSTM)分类
信息技术与安全科学引用本文复制引用
王艳超,姚江毅,李雄伟,刘林云..基于TCN模型的软件系统老化预测框架[J].计算机应用与软件,2025,42(5):25-29,61,6.基金项目
国家自然科学基金项目(62071483). （62071483）
