Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A review of data-driven approaches for prediction and classification of building energy consumption
2017602 citationsYixuan Wei, Xingxing Zhang et al.Renewable and Sustainable Energy Reviewsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Xiaoyun Zhao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiaoyun Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoyun Zhao more than expected).
This network shows the impact of papers produced by Xiaoyun Zhao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiaoyun Zhao. The network helps show where Xiaoyun Zhao may publish in the future.
Co-authorship network of co-authors of Xiaoyun Zhao
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoyun Zhao.
A scholar is included among the top collaborators of Xiaoyun Zhao based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Xiaoyun Zhao. Xiaoyun Zhao is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhao, Xiaoyun, et al.. (2022). Identifying models for assessing the system-level impacts of Mobility as a Service (MaaS). SPIRE - Sciences Po Institutional REpository.1 indexed citations
Zhao, Xiaoyun, et al.. (2020). Values of MaaS potential impacts based on Representative Scenarios. KTH Publication Database DiVA (KTH Royal Institute of Technology).1 indexed citations
9.
Karlsson, MariAnne, et al.. (2019). A National Approach to Assessing the Impacts of Mobility-as-a-Service (MaaS). Chalmers Research (Chalmers University of Technology).3 indexed citations
Wei, Yixuan, Xingxing Zhang, Yong Shi, et al.. (2017). A review of data-driven approaches for prediction and classification of building energy consumption. Renewable and Sustainable Energy Reviews. 82. 1027–1047.602 indexed citations breakdown →
13.
Zhao, Xiaoyun, et al.. (2017). An evaluation of the reliability of GPS-based transportation data. Dalarna University College Electronic Archive. 323–334.1 indexed citations
Zhao, Xiaoyun. (2017). Government vs Market in Sustainable Residential Development? : Microdata analysis of car travel, CO2 emission and residence location. Dalarna University College Electronic Archive.
16.
Zhao, Xiaoyun, et al.. (2016). Residential planning, driver mobility and CO2 emission. Dalarna University College Electronic Archive.
Attia, Mohamed, et al.. (2011). Assisting personal positioning in indoor environments using map matching. Archives of Photogrammetry Cartography and Remote Sensing. 22. 39–49.3 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.