المؤلفون: Huijun Liang, Chenhao Lin, Aokang Pang

المصدر: International Journal of Electrical Power & Energy Systems, Vol 159, Iss , Pp 110033- (2024)

مصطلحات موضوعية: Unit commitment, Reinforcement learning, Knowledge data-driven, Surrogate model, Meta-heuristic algorithm, Production of electric energy or power. Powerplants. Central stations, TK1001-1841

وصف الملف: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S0142061524002540; https://doaj.org/toc/0142-0615

URL الوصول: https://doaj.org/article/34473a8faa734d6c8e8d08677bfc3277

المؤلفون: Chenhao Lin, Huijun Liang, Aokang Pang, Jianwei Zhong, Yongchao Yang

المصدر: Journal of Modern Power Systems and Clean Energy, Vol 12, Iss 1, Pp 52-64 (2024)

مصطلحات موضوعية: Multi-area combined economic/emission dispatch, high-dimensional power system, deep belief network, data driven, transfer learning, Production of electric energy or power. Powerplants. Central stations, TK1001-1841, Renewable energy sources, TJ807-830

وصف الملف: electronic resource

Relation: https://ieeexplore.ieee.org/document/10250161/; https://doaj.org/toc/2196-5420

URL الوصول: https://doaj.org/article/59e3e546283d422b91b39d1b912fa89e

المؤلفون: Chenhao Lin, Huijun Liang, Aokang Pang, Jianwei Zhong

المصدر: Frontiers in Energy Research, Vol 11 (2023)

مصطلحات موضوعية: combined economic/emission dispatch, data-driven, genetic algorithm, surrogate model, computationally expensive optimization problems, General Works

وصف الملف: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fenrg.2023.1273760/full; https://doaj.org/toc/2296-598X

URL الوصول: https://doaj.org/article/19dbca96db774ab8ae67622237431137

المؤلفون: Chenhao Lin, Kumar, Ajay

المصدر: 2016 23rd International Conference on Pattern Recognition (ICPR) Pattern Recognition (ICPR), 2016 23rd International Conference on. :943-948 Dec, 2016

Relation: 2016 23rd International Conference on Pattern Recognition (ICPR)

المؤلفون: Chenhao Lin, Zhonghan Sun, Zhendong Mei, Hailuan Zeng, Manying Zhao, Jianying Hu, Mingfeng Xia, Tao Huang, Chaolong Wang, Xin Gao, Yan Zheng

المصدر: BMC Medicine, Vol 20, Iss 1, Pp 1-11 (2022)

مصطلحات موضوعية: Blood pressure, Hypertension, Amino acids, Metabolomics, Mendelian randomization, Medicine

وصف الملف: electronic resource

Relation: https://doaj.org/toc/1741-7015

URL الوصول: https://doaj.org/article/d8c70d35ceea461aba1a04a8e9597b62

المؤلفون: Jianying Hu, Manying Zhao, Chenhao Lin, Zhonghan Sun, Guo-Chong Chen, Zhendong Mei, Yan Zheng

المصدر: Nutrition & Metabolism, Vol 19, Iss 1, Pp 1-11 (2022)

مصطلحات موضوعية: Visceral adipose tissue, Bone mineral density, Fracture, Mendelian randomization, UK Biobank, Nutrition. Foods and food supply, TX341-641, Nutritional diseases. Deficiency diseases, RC620-627

وصف الملف: electronic resource

Relation: https://doaj.org/toc/1743-7075

URL الوصول: https://doaj.org/article/c694c207af074447b8804f83131154cc

المؤلفون: Huijun Liang, Aokang Pang, Chenhao Lin, Jianwei Zhong

المصدر: IGI Global, International Journal of Swarm Intelligence Research (IJSIR). 15(1):1-29

الإتاحة: https://ideas.repec.org/a/igg/jsir00/v15y2024i1p1-29.html

المؤلفون: Aokang Pang, Huijun Liang, Chenhao Lin, Lei Yao

المصدر: Energies, Vol 16, Iss 2, p 1011 (2023)

مصطلحات موضوعية: economic dispatch, power system, surrogate-assisted bat algorithm, general regression neural network, Technology

وصف الملف: electronic resource

Relation: https://www.mdpi.com/1996-1073/16/2/1011; https://doaj.org/toc/1996-1073

URL الوصول: https://doaj.org/article/99969ecce6d047b692f5f694fd217e97

المؤلفون: SICONG HAN, CHENHAO LIN, CHAO SHEN, QIAN WANG, XIAOHONG GUAN

المصدر: ACM Computing Surveys; 2023 Suppl14s, Vol. 55, p1-38, 38p, 2 Illustrations

مصطلحات موضوعية: DEEP learning, TECHNOLOGICAL progress

المؤلفون: Qian Li, Chao Shen, Qingyuan Hu, Chenhao Lin, Xiang Ji, Saiyu Qi

المصدر: IEEE Transactions on Dependable and Secure Computing. :1-13

مصطلحات موضوعية: Electrical and Electronic Engineering

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::a327ede08c82aee2820efaef54b3f30f
https://doi.org/10.1109/tdsc.2022.3184594