BIM实验研究中心

位置: 首页 > 科研成果 > 期刊论文 > 正文

BIM中心2019年期刊论文汇总

BIM中心 发表于: 2019-09-10 10:00 点击:[]

[1] Jiayuan Wang, Bo Yu, Vivian W.Y. Tam, Jie Li, Xiaoxiao Xu. Critical factors affecting willingness of design units towards construction waste minimization: An empirical study in Shenzhen, China[J]. Journal of Cleaner Production (SCI中科院一区,Top期刊), 2019 (221), 526-535.

[2] Bo Yu, Jiayuan Wang*, Jie Li, Jingrong Zhang, Yani Lai, Xiaoxiao Xu. Prediction of large-scale demolition waste generation during urban renewal: A hybrid trilogy method [J]. Waste Management (SCI中科院二区), 2019 (89), 1-9.

[3] Jiayuan Wang, Huanyu Wu, Vivian W.Y.Tam, Jian Zuo. Considering life-cycle environmental impacts and society's willingness for optimizing construction and demolition waste management fee: An empirical study of China[J]. Journal of Cleaner Production (SCI中科院一区,Top期刊), 2019 (206), 1004-1014.

[4] Kui Shan, Cheng Fan, Jiayuan Wang*. Model predictive control for thermal energy storage assisted large central cooling systems[J]. Energy (SCI中科院二区,Top期刊), 2019, Accepted.

[5] Xiaoxiao Xu, Clyde Zhengdao Li* et al. Collaboration between designers and contractors to improve building energy performance. Journal of Cleaner Production. 2019, 219:20-32.

[6] Cheng Fan, Yongjun Sun, Yang Zhao, Mengjie Song, Jiayuan Wang. Deep learning-based feature engineering methods for improved building energy prediction. Applied Energy. 2019, 240: 35-45.

[7] Cheng Fan, Jiayuan Wang, Wenjie Gang*, Shenghan Li. Assessment of deep recurrent neural network-based strategies for short-term building energy predictions. Applied Energy. 2019, 236: 700-710.

[8] Cheng Fan, Fu Xiao, Chengchu Yan, Chengliang Liu, Zhengdao Li, Jiayuan Wang. A novel methodology to explain and evaluate data-driven building energy performance models based on interpretable machine learning. Applied Energy. 2019, 235: 1551-60.

[9] Pei Huang, Cheng Fan*, Xingxing Zhang, Jiayuan Wang. A hierarchical coordinated demand response control for buildings with improved performances at building group. Applied Energy. 2019, 242: 684-694.

[10] Ding Zhikun, Liu Shan, Liao Longhui, Zhang Liang. A digital construction framework integrating building information modeling and reverse engineering technologies for renovation projects [J]. Automation in Construction, 102, pp.45-58, 2019, EI,SCI(Q1)

[11] Q. Wang, Y. Tan*, Z. Mei, 2019, Computational Methods of Acquisition and Processing of 3D Point Cloud Data for Construction Applications, Archives of Computational Methods in Engineering. (JCR Q1,IF=6.605, Top期刊)

[12] Ding, Z., Liu, S., Liao, L.*, and Zhang, L. (2019). A digital construction framework integrating building information modeling and reverse engineering technologies for renovation projects. Automation in Construction, 102, 45-58.

[13] Liao, L.*, and Teo, E.A.L. (2019). Managing critical drivers for building information modelling implementation in the Singapore construction industry: an organizational change perspective. International Journal of Construction Management, 19(3), 240-256.

[14] Wu Z, Yu ATW, Wang H, Wei Y, Driving Factors for Construction Waste Minimization: Empirical Studies in Hong Kong and Shenzhen, J. Green Build. (2019) (in press).

[15] Wu Z, Yu ATW, Poon CS, An off-site snapshot methodology for estimating building construction waste composition - a case study of Hong Kong, Environ. Impact Assess. Rev. 77 (2019) 128-35.

[16] Wu Z, Li H, Feng Y, Luo X, Chen Q, Developing a green building evaluation standard for interior decoration: A case study of China, Build. Environ. 152 (2019) 50-8.

[17] Wang J, Shen L, Ren Y, Ochoa JJ, Guo Z, Yan H, et al., A lessons mining system for searching references to support decision making towards sustainable urbanization, J. Cleaner Prod. 209 (2019) 451-60.

[18] Luo X, Li H, Wang H, Wu Z, Dai F, Cao D, Vision-based detection and visualization of dynamic workspaces, Autom. Constr. 104 (2019) 1-13.

[19] Huo X, Yu ATW, Darko A, Wu Z, Critical factors in site planning and design of green buildings: A case of China, J. Cleaner Prod. 222 (2019) 685-94.

[20] Hong J, Tang M, Wu Z, Miao Z, Shen GQ, The evolution of patterns within embodied energy flows in the Chinese economy: A multi-regional-based complex network approach, Sustain. Cities Soc. 47 (2019) 101500.

上一条:BIM中心2018年期刊论文汇总

关闭

深圳大学 土木与交通工程学院

中澳BIM与智慧建造联合研究中心/深圳大学建筑互联网与BIM实验中心

地址:广东省深圳市南山区深圳大学南区土木与交通工程学院2楼

邮编:518060   电话:0755-26535528

中心公众号

网站访问量: