Ranran Li | Environmental Science | Young Scientist Award

Published on by Phenomenological Research Awards

Mr. Ranran Li | Environmental Science | Young Scientist Award 

Associate Professor at Yanshan University | China

Mr. Ranran Li is a distinguished scholar and master supervisor who received his Ph.D. in Economics from Dongbei University of Finance and Economics and is recognized as an excellent talent under the Yanshan Scholars program at Yanshan University. As a CCF member, he has built an influential research profile with 1,254 citations across 1,074 documents, 28 publications, and an h-index of 16, reflecting the high impact of his work, and his scholarly contributions continue to influence the field despite the View h-index button being disabled in preview mode. Professionally, Mr. Ranran Li serves as an anonymous reviewer for leading journals including Technovation, Technological Forecasting and Social Change, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Neural Networks and Learning Systems, Applied Energy, Energy, Journal of Cleaner Production, and many others, demonstrating his authority and expertise in his domain. His research interests encompass energy demand forecasting, environmental comprehensive evaluation, financial risk early-warning, and air pollution monitoring and management, with extensive experience leading projects funded by national and provincial foundations, including studies on air environment governance, urban environmental system evaluation, carbon emission rights allocation, and wind energy resource assessment using machine learning and intelligent optimization algorithms. He has also guided students to success in national and international modeling competitions, exemplifying his mentorship in applied research and mathematical modeling. Mr. Ranran Li’s research skills include multi-objective optimization, fuzzy synthetic evaluation, hybrid forecasting models, support vector machines, neural networks, and data-driven predictive modeling, enabling him to address complex problems in energy, environment, and financial systems. His numerous publications in top-tier journals, along with his awards and recognition for scientific excellence, highlight his scholarly impact. In conclusion, Mr. Ranran Li exemplifies a combination of rigorous scholarship, innovative research, and effective mentorship, establishing him as a leading researcher whose contributions advance knowledge and practice across energy, environmental, and financial risk domains.

Profile: Scopus | Orcid

Featured Publications:

  • Li, R., & Jin, Y. (2018). A wind speed interval prediction system based on multi-objective optimization for machine learning method. Applied Energy, 228, 2207–2220.

  • Jiang, P., Li, R., et al. (2020). A novel composite electricity demand forecasting framework by data processing and optimized support vector machine. Applied Energy, 260, 114243.

  • Li, R., & Jin, Y. (2018). The early-warning system based on hybrid optimization algorithm and fuzzy synthetic evaluation model. Information Sciences, 435, 296–319.

  • Li, R., Dong, Y., Zhu, Z., et al. (2019). A dynamic evaluation framework for ambient air pollution monitoring. Applied Mathematical Modelling, 65, 52–71. https://doi.org/10.1016/j.apm.2018.07.052

  • Li, R., Hu, Y., Heng, J., & Chen, X. (2021). A novel multiscale forecasting model for crude oil price time series. Technological Forecasting and Social Change, 173, 121181.

  • Li, R., Chen, X., Balezentis, T., Streimikiene, D., & Niu, Z. (2021). Multi-step least squares support vector machine modeling approach for forecasting short-term electricity demand with application. Neural Computing & Applications, 33, 301–320.

  • Li, R., Jiang, P., et al. (2020). A novel hybrid forecasting scheme for electricity demand time series. Sustainable Cities and Society, 55, 102036