A Novel Hybridization of Artificial Neural Networks and ARIMA Models for Forecasting Resource Consumption in an IIS Web Server. - Yongquan Yan; Ping Guo 002; Lifeng Liu (ISSRE Workshops, 2014)

A Practice of Forecasting Software Aging in an IIS Web Server Using SVM. - Yongquan Yan; Ping Guo 002; Lifeng Liu (ISSRE Workshops, 2014)

Predicting Software Abnormal State by using Classification Algorithm. - Yongquan Yan; Ping Guo 002 (J. Database Manag., 2016)

使用混合模型预测Web服务器中的资源消耗 (Predicting Resource Consumption in Web Server Using Hybrid Model). - Yongquan Yan; Ping Guo (计算机科学, 2016)

Variance analysis of software ageing problems. - Yongquan Yan (IET Softw., 2018)

An experimental case study on the relationship between workload and resource consumption in a commercial web server. - Yongquan Yan; Ping Guo 002; Bin Cheng; Zhigao Zheng 001 (J. Comput. Sci., 2018)

Software ageing prediction using neural network with ridge. - Yongquan Yan (IET Softw., 2020)

Software Aging Forecast Using Recurrent SOM with Local Model. - Yongquan Yan (J. Inf. Technol. Res., 2020)

Performance Analysis Using a Deep Belief Network by a Self-Organizing Map. - Yongquan Yan; Yu Zhu; Yanjun Li (Int. J. Comput. Intell. Appl., 2021)

Predicting Software Aging With a Hybrid Weight-Based Method. - Yongquan Yan; Yanjun Li; Bin Cheng (J. Inf. Technol. Res., 2021)

Performance analysis with self-organizing map and recurrent neural network. - Yongquan Yan (Int. J. Model. Simul. Sci. Comput., 2022)

Improving college ideological and political education based on deep learning. - Youwu Zhang; Yongquan Yan; R. Lakshmana Kumar; Sapna Juneja (Int. J. Inf. Commun. Technol., 2024)