参考文献/References:
[1]谭洪卫,徐钰琳,胡承益,等.全球气候变化应对与我国高校校园建筑节能监管[J].建筑热能通风空调,2010,29(1):36-40.
TAN Hongwei, XU Yulin,HU Chengyi, et al. Research on building campus energy management[J].Building Energy & Environment, 2010,29(1):36-40.
[2]YAN Ding, WANG Qiaochu, WANG Zhaoxia, et al. An occupancy-based model for building electricity consumption prediction: A case study of three campus buildings in Tianjin[J]. Energy & Buildings,2019,202:109412.
[3]高彪,谭洪卫,宋亚超.高校校园建筑用能现状及存在问题分析——以长三角地区某综合型大学为例[J].建筑节能,2011,39(2):41-44.
GAO Biao, TAN Hongwei, SONG Yachao. Campus building energy consumption: Taking one comprehensive university as example[J]. Building Energy Efficiency, 2011,39(2):41-44.
[4]CHUNG Min Hee,RHEE Eon Ku. Potential opportunities for energy conservation in existing buildings on university campus: A field survey in Korea[J]. Energy & Buildings,2014,78: 176-182.
[5]WALTER Leal Filho, AMANDA Lange Salvia, ARMINDA do Paço, et al. A comparative study of approaches towards energy efficiency and renewable energy use at higher education institutions[J]. Journal of Cleaner Production,2019,237:117728.
[6]WANG Y, SHAO L. Understanding occupancy pattern and improving building energy efficiency through Wi-Fi based indoor positioning[J].Building and Environment, 2017, 45(3): 53.
[7]王茜. 西北某高校图书馆能耗预测模型与节能策略研究[D].西安:西安建筑科技大学,2021.
WANG Qian. Energy consumption prediction model and energy saving strategy research of a university library in northwest China[D]. Xi'an:Xi'an Univ. of Arch. & Tech.,2021.
[8]YIK F W H,Burnett J,Prescott I. Predicting air-conditioning energy consumption of a group of buildings using different heat rejection methods[J]. Energy & Buildings,2001,33(2): 151-166
[9]SEPEHR M, EGHTEDAEI R, TOOLABIMOGHADAM A, et al. Modeling the electrical energy consumption profile for residential buildings in Iran[J]. Sustainable Cities and Society, 2018, 41(10): 481-489.
[10]MERIH Aydinalp,V. ISMET Ugursal,ALAN S. Fung. Modeling of the appliance, lighting, and space-cooling energy consumptions in the residential sector using neural networks[J]. Applied Energy,2002,71(2): 87-110
[11]ALBERTO Hernandez Neto, FLÁVIO Augusto Sanzovo Fiorelli. Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption[J]. Energy & Buildings,2008,40(12): 2169-2176
[12]LI Q, REN P, MENG Q. Prediction model of annual energy consumption of residential buildings[C]//2010 International Conference on Advances in Energy Engineering. Beijing:ICAEE,2010.
[13]谈力. 基于相似日选取的小波极限学习机短期负荷预测模型研究[D].南京:南京理工大学,2015.
TAN Li. Short-term power load forecasting based on similar days and extreme learning machine[D].Nanjing:Nanjing University of Science & Technology,2015.
[14]张悦. 某大型公共建筑能耗分形特性与预测模型研究[D].西安:西安建筑科技大学,2019.
ZHANG Yue. Studies on fractal characteristics and forecasting model of energy consumption of a large public building[D]. Xi'an:Xi'an Univ. of Arch. & Tech., 2019.
[15]黄豪彩,黄宜坚,杨冠鲁. 基于LM算法的神经网络系统辨识[J]. 组合机床与自动化加工技术, 2003(2): 6-8.
HUANG Haocai, HUANG Yijian,YANG Guanlu. Neural networksystem identification based onlevenberg-marquardt algorithm[J]. Modular Machine Tool & Automatic Manufacturing Technique, 2003(2): 6-8.
[16]QIAO J,WANG L,YANG C,et al. Adaptive leven bergmarquardt algorithm based echo state network for chaotic time series prediction[ J]. IEEE Access,2018,6:10720-10732.
[17]杨雪. 基于深度学习的大型公建能耗预测及信息管理系统研究[D].西安:西安建筑科技大学,2019.
YANG Xue. Study on energy consumption prediction and information management system based on deep learning for large-scale public building[D]. Xi'an: Xi'an Univ. of Arch. & Tech., 2019.
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