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.
Modeling of solar energy systems using artificial neural network: A comprehensive review
2019568 citationsGuilan Wang, Haiou Zhang et al.profile →
Deep learning based online metallic surface defect detection method for wire and arc additive manufacturing
2022162 citationsHaiou Zhang, Guilan Wang et al.Robotics and Computer-Integrated Manufacturingprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Guilan Wang'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 Guilan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guilan Wang more than expected).
This network shows the impact of papers produced by Guilan Wang. 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 Guilan Wang. The network helps show where Guilan Wang may publish in the future.
Co-authorship network of co-authors of Guilan Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Guilan Wang.
A scholar is included among the top collaborators of Guilan Wang 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 Guilan Wang. Guilan Wang is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhang, Haiou, et al.. (2022). Deep learning based online metallic surface defect detection method for wire and arc additive manufacturing. Robotics and Computer-Integrated Manufacturing. 80. 102470–102470.162 indexed citations breakdown →
9.
Wang, Guilan, et al.. (2016). Fast Clustering and Anomaly Detection Technique for Large-scale Power Data Stream. 40(24). 33.4 indexed citations
10.
Wang, Guilan. (2010). Rapid Manufacturing Prototype Technology Based on Industrial Robot. Machine Tool & Hydraulics.1 indexed citations
11.
Wang, Guilan. (2009). The design of starting circuit of HID lamp. Hebei Nongye Daxue xuebao.1 indexed citations
12.
Chen, Hu, et al.. (2007). [Diethylstilbestrol intervention in carcinogenesis of breast cancer in wistar rats].. PubMed. 26(6). 596–600.1 indexed citations
13.
Wang, Guilan. (2007). Thinking about management of nursing error. Zhonghua huli zazhi.2 indexed citations
14.
Wang, Guilan. (2007). Design of metal component directly fabricating system based on plasma arc welding. Electric Welding Machine.1 indexed citations
15.
Wang, Guilan. (2006). Research of Robotic Automatic Polishing System for Plasma Spray Rapid Mould.3 indexed citations
Wang, Guilan, et al.. (2005). Establishment of rapid propagation system of aerial root segments of anthurium andraeanum. Chih Wu Sheng Li Hsueh T'ung Hsun. 41(3). 297–301.1 indexed citations
18.
Wang, Guilan, et al.. (2004). Syntheses of novel p-phenylenediethenylenedicyanine dyes. Chemical Research and Application.1 indexed citations
Wang, Guilan. (2001). The computational Simulation by Elasto-Plastic FEM for the Laying of Metal Wire Rope.1 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.