A Novel Hybrid Approach with A Decomposition Method and The RVFL Model for Crude Oil Price Prediction. - Chengyuan Zhang 003; Fuxin Jiang; Shouyang Wang; Wei Shang (IEEE BigData, 2020)

A Novel Hybrid Framework for Hourly PM2.5 Concentration Forecasting Using CEEMDAN and Deep Temporal Convolutional Neural Network. - Fuxin Jiang; Chengyuan Zhang 003; Shaolong Sun; Jingyun Sun (CoRR, 2020)

Forecasting hourly PM2.5 based on deep temporal convolutional neural network and decomposition method. - Fuxin Jiang; Chengyuan Zhang 003; Shaolong Sun; Jingyun Sun (Appl. Soft Comput., 2021)

Air quality forecasting with artificial intelligence techniques: A scientometric and content analysis. - Yanzhao Li; Ju'e Guo; Shaolong Sun; Jianing Li; Shouyang Wang; Chengyuan Zhang 003 (Environ. Model. Softw., 2022)

Improving multi-step ahead tourism demand forecasting: A strategy-driven approach. - Shaolong Sun; Zongjuan Du; Chengyuan Zhang 003; Shouyang Wang (Expert Syst. Appl., 2022)

Multi-step ahead tourism demand forecasting: The perspective of the learning using privileged information paradigm. - Shaolong Sun; Mingchen Li; Shouyang Wang; Chengyuan Zhang 003 (Expert Syst. Appl., 2022)

How to capture tourists' search behavior in tourism forecasts? A two-stage feature selection approach. - Shaolong Sun; Mengyuan Hu; Shouyang Wang; Chengyuan Zhang 003 (Expert Syst. Appl., 2023)

A novel hybrid model for crude oil price forecasting based on MEEMD and Mix-KELM. - Jingjing Li; Zhanjiang Hong; Chengyuan Zhang 003; Jiaqian Wu; Cuicui Yu (Expert Syst. Appl., 2024)

Forecasting tourism demand with a novel robust decomposition and ensemble framework. - Xin Li; Xu Zhang; Chengyuan Zhang 003; Shouyang Wang (Expert Syst. Appl., 2024)