A5071338170- Market Dynamics and Volatility
- Stock Market Forecasting Methods
- Traditional Chinese Medicine Studies
- Machine Learning in Healthcare
- Climate Change Policy and Economics
- Artificial Intelligence in Healthcare
- Grey System Theory Applications
- Energy Load and Power Forecasting
- Integrated Energy Systems Optimization
- Energy, Environment, Economic Growth
- Environmental Impact and Sustainability
Taiyuan Normal University
2024
China University of Petroleum, Beijing
2022-2023
China National Petroleum Corporation (China)
2022
Compared with retail prices of state-owned companies used in almost all existing studies, China's refined oil wholesale private enterprises and local refineries are more affected by the market better reflect real supply-demand situation. For first time, this paper applies own-monitored daily-frequency during 2013–2020 to derive spillover effects international crude on through VAR-BEKK-GARCH (vector autoregression-Baba, Engle, Kraft, Kroner-generalized autoregressive conditional...
With the acceleration of global response to climate change, China announced world in 2020 goals carbon peaking by 2030 and neutrality 2060, which reflects its firm determination implement Intended Nationally Determined Contributions. Energy transition is key achieving goals. It great theoretical practical significance study impact low energy on China?s macro-economy under Based three scenarios, this paper uses dynamic computable general equilibrium model simulate estimate different pathways...
In this paper, a new prediction model for accurately recognizing and appropriately evaluating the trends of domestic chemical products improving forecasting accuracy products’ prices is proposed. The proposed uses minimum error as evaluation objective to forecast settlement price. Active contracts polyethylene polypropylene futures on Dalian Commodity Futures Exchange next five days were used, data divided into training set test through normalization, time window, batch processing size,...
Diabetes is a chronic disease, which characterized by abnormally high blood sugar levels. It may affect various organs and tissues, even lead to life-threatening complications. Accurate prediction of diabetes can significantly reduce its incidence. However, the current methods struggle accurately capture essential characteristics nonlinear data, black-box nature these hampers clinical application. To address challenges, we propose KCCAM_DNN, method that integrates Kendall’s correlation...