Faculty&Schools

Faculty&Schools
Faculty&Schools SCHOOL OF ELECTRICAL ENGINEERING Doctoral Supervisors

Doctoral Supervisors

Ling-Ling Li (李玲玲)
EMAIL:lilinglinglaoshi@126.com
RESEARCH INTERESTS
1)Electrical apparatus reliability

Reliability measurement and life prediction of electrical products and systems.

2)Electric power system and its automation

Monitoring and control of power systems.

3)Computational intelligence and its application

Evolutionary algorithms, Rough set theory, Bayesian inference, Deep learning, support vector machines, etc.

4)Artificial intelligence and knowledge engineering

Knowledge representation, reasoning, organization and automatic acquisition.
Representative academic achievements
(1) Ling-Ling Li(李玲玲), Yu-Wei Liu, Ming-Lang Tseng, et al. Reducing environmental pollution and fuel consumption using optimization algorithm to develop combined cooling heating and power system operation strategies. Journal of Cleaner Production. 2019. ISSN 0959-6526. Impact factor of the journal :6.395;SCI: Q1

(2) Ling-Ling Li (李玲玲), Xue Zhao, Ming-Lang Tseng, Raymond R. Tan. Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm. Journal of Cleaner Production. Volume 242, 1 January 2020, 118447. ISSN 0959-6526. Impact factor of the journal :6.395;SCI: Q1. (WOS: 000491240100110)

(3) Ling-Ling Li (李玲玲), Shi-Yu Wen, Ming-Lang Tseng, Cheng-Shan Wang. Renewable energy prediction: A novel short-term prediction model of photovoltaic output power. Journal of Cleaner Production. 2019, 228: 359-375. ISSN 0959-6526. Impact factor of the journal :6.395;SCI:Q1. (WOS: 000470947000032)

(4) Ling-Ling Li (李玲玲), Jin Sun, Ching-Hsin Wang, Zhou Yatong, Kuo-Ping Lin. Enhanced Gaussian Process Mixture Model for Short-Term Electric Load Forecasting Information Sciences, 2019, 477: 386-398. ISSN 0020-0255. Impact factor of the journal :5.524; SCI:Q1. (WOS: 000456763600026)

(5) Ling-Ling Li(李玲玲), Zhi-Feng Liu, Ming-Lang Tseng, Anthony S.F. Chiu. Enhancing the Lithium-ion battery life predictability using a hybrid method. Applied Soft Computing, 2019,74: 110-121.ISSN 1568-4946. Impact factor of the journal :4.873; SCI:Q1. (WOS:000454251200009)