Classification based on Data Envelopment Analysis and supervised learning: A case study on energy performance of residential buildings

Author(s):  
Anjana Gupta ◽  
Mohit Kohli ◽  
Navdha Malhotra
2018 ◽  
Vol 17 (05) ◽  
pp. 1429-1467 ◽  
Author(s):  
Mohammad Amirkhan ◽  
Hosein Didehkhani ◽  
Kaveh Khalili-Damghani ◽  
Ashkan Hafezalkotob

The issue of efficiency analysis of network and multi-stage systems, as one of the most interesting fields in data envelopment analysis (DEA), has attracted much attention in recent years. A pure serial three-stage (PSTS) process is a specific kind of network in which all the outputs of the first stage are used as the only inputs in the second stage and in addition, all the outputs of the second stage are applied as the only inputs in the third stage. In this paper, a new three-stage DEA model is developed using the concept of three-player Nash bargaining game for PSTS processes. In this model, all of the stages cooperate together to improve the overall efficiency of main decision-making unit (DMU). In contrast to the centralized DEA models, the proposed model of this study provides a unique and fair decomposition of the overall efficiency among all three stages and eliminates probable confusion of centralized models for decomposing the overall efficiency score. Some theoretical aspects of proposed model, including convexity and compactness of feasible region, are discussed. Since the proposed bargaining model is a nonlinear mathematical programming, a heuristic linearization approach is also provided. A numerical example and a real-life case study in supply chain are provided to check the efficacy and applicability of the proposed model. The results of proposed model on both numerical example and real case study are compared with those of existing centralized DEA models in the literature. The comparison reveals the efficacy and suitability of proposed model while the pitfalls of centralized DEA model are also resolved. A comprehensive sensitivity analysis is also conducted on the breakdown point associated with each stage.


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1049
Author(s):  
Zhang Deng ◽  
Yixing Chen ◽  
Xiao Pan ◽  
Zhiwen Peng ◽  
Jingjing Yang

Urban building energy modeling (UBEM) is arousing interest in building energy modeling, which requires a large building dataset as an input. Building use is a critical parameter to infer archetype buildings for UBEM. This paper presented a case study to determine building use for city-scale buildings by integrating the Geographic Information System (GIS) based point-of-interest (POI) and community boundary datasets. A total of 68,966 building footprints, 281,767 POI data, and 3367 community boundaries were collected for Changsha, China. The primary building use was determined when a building was inside a community boundary (i.e., hospital or residential boundary) or the building contained POI data with main attributes (i.e., hotel or office building). Clustering analysis was used to divide buildings into sub-types for better energy performance evaluation. The method successfully identified building uses for 47,428 buildings among 68,966 building footprints, including 34,401 residential buildings, 1039 office buildings, 141 shopping malls, and 932 hotels. A validation process was carried out for 7895 buildings in the downtown area, which showed an overall accuracy rate of 86%. A UBEM case study for 243 office buildings in the downtown area was developed with the information identified from the POI and community boundary datasets. The proposed building use determination method can be easily applied to other cities. We will integrate the historical aerial imagery to determine the year of construction for a large scale of buildings in the future.


Water Policy ◽  
2018 ◽  
Vol 21 (1) ◽  
pp. 49-72 ◽  
Author(s):  
Jiazhong Zheng ◽  
Weiguang Wang ◽  
Dan Chen ◽  
Xinchun Cao ◽  
Wanqiu Xing ◽  
...  

Abstract A coordinated nexus of agricultural resources is vital to achieve food security and sustainable development in China. Comprehensively considering the water–energy–food nexus as well as the external environment, this study adopts a three-stage data envelopment analysis (DEA) modelling evaluation method to assess the agricultural production efficiency (APE) of seven provinces in the middle and lower reaches of the Yangtze River (MLYR) during 1996–2015. The results show that the three-stage DEA modelling evaluation method reveals real APE and is considered to be a better quantitative method than conventional approaches. A gradually widening range of APE is an important challenge for this region. Significantly, this region generates huge demands for agricultural resources. Moreover, regional emissions of greenhouse gases (GHG) decreased from 34.20 million tons standard coal in 1996 to 32.11 million tons standard coal in 2015, though APE has continued to decrease by 2.56% in the past two decades. In general, the management and technology levels should be improved simultaneously, even though specific opportunities for APE improvement vary across provinces in MLYR. However, understanding the temporal and spatial variation of APE along with the WEF nexus from a production-based insight is a vital step toward appropriately targeted policy making for nationwide resources savings and emissions reduction.


10.19082/3266 ◽  
2016 ◽  
Vol 8 (11) ◽  
pp. 3266-3271
Author(s):  
Mohammad Meskarpour Amiri ◽  
Taha Nasiri ◽  
Seyed Hassan Saadat ◽  
Hosein Amini Anabad ◽  
Payman Mahboobi Ardakan

Author(s):  
Hadi Shirouyehzad ◽  
F. Hosseinzadeh Lotfi ◽  
Mir. B. Aryanezhad ◽  
Reza Dabestani

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