Yimin Mao

739 total citations · 1 hit paper
39 papers, 318 citations indexed

About

Yimin Mao is a scholar working on Management, Monitoring, Policy and Law, Global and Planetary Change and Safety, Risk, Reliability and Quality. According to data from OpenAlex, Yimin Mao has authored 39 papers receiving a total of 318 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Management, Monitoring, Policy and Law, 13 papers in Global and Planetary Change and 10 papers in Safety, Risk, Reliability and Quality. Recurrent topics in Yimin Mao's work include Landslides and related hazards (18 papers), Geotechnical Engineering and Analysis (10 papers) and Flood Risk Assessment and Management (9 papers). Yimin Mao is often cited by papers focused on Landslides and related hazards (18 papers), Geotechnical Engineering and Analysis (10 papers) and Flood Risk Assessment and Management (9 papers). Yimin Mao collaborates with scholars based in China, United States and Iran. Yimin Mao's co-authors include Yaser A. Nanehkaran, Maosheng Zhang, Deborah Simon Mwakapesa, Mohammad Azarafza, Fei Teng, Reza Derakhshani, Liang Chen, Genlong Wang, Pingping Sun and Kaibin Xu and has published in prestigious journals such as PLoS ONE, Scientific Reports and Sustainability.

In The Last Decade

Yimin Mao

35 papers receiving 309 citations

Hit Papers

Utilizing Hybrid Machine Learning and Soft Computing Tech... 2024 2026 2025 2024 10 20 30 40 50
What are hit papers?

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.

  1. Utilizing Hybrid Machine Learning and Soft Computing Techniques for Landslide Susceptibility Mapping in a Drainage Basin
    2024 55 citations Yimin Mao, Fei Teng et al. Water profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yimin Mao China 11 206 127 87 61 40 39 318
Jiale Wang China 6 205 1.0× 137 1.1× 63 0.7× 66 1.1× 33 0.8× 14 336
Songlin Liu China 8 242 1.2× 112 0.9× 94 1.1× 74 1.2× 90 2.3× 19 379
Mehdi Azarafza Iran 5 280 1.4× 150 1.2× 92 1.1× 83 1.4× 75 1.9× 5 369
Alihan Teke Türkiye 5 177 0.9× 132 1.0× 52 0.6× 59 1.0× 57 1.4× 11 364
Shivani Chauhan India 5 246 1.2× 177 1.4× 59 0.7× 62 1.0× 22 0.6× 7 325
Shiluo Xu China 6 306 1.5× 137 1.1× 61 0.7× 104 1.7× 136 3.4× 8 399
Ling Han China 10 124 0.6× 109 0.9× 28 0.3× 56 0.9× 17 0.4× 25 322
Giulia Bossi Italy 12 217 1.1× 75 0.6× 60 0.7× 89 1.5× 94 2.4× 38 351
Arip Syaripudin Nur South Korea 7 156 0.8× 172 1.4× 34 0.4× 46 0.8× 27 0.7× 12 310
Wahyu Luqmanul Hakim South Korea 10 216 1.0× 139 1.1× 21 0.2× 95 1.6× 31 0.8× 19 416

Countries citing papers authored by Yimin Mao

Since Specialization
Citations

This map shows the geographic impact of Yimin Mao'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 Yimin Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yimin Mao more than expected).

Fields of papers citing papers by Yimin Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yimin Mao. 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 Yimin Mao. The network helps show where Yimin Mao may publish in the future.

Co-authorship network of co-authors of Yimin Mao

This figure shows the co-authorship network connecting the top 25 collaborators of Yimin Mao. A scholar is included among the top collaborators of Yimin Mao 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 Yimin Mao. Yimin Mao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Feng, Li, Yimin Mao, Hao Liu, et al.. (2025). Convolutional neural network-based deep learning for landslide susceptibility mapping in the Bakhtegan watershed. Scientific Reports. 15(1). 13250–13250. 3 indexed citations
2.
3.
Mao, Yimin, et al.. (2024). Adaptive modeling of landslide susceptibility using Analytical Hierarchy Process and Multi-Objective Decision Optimization. Advances in Space Research. 75(6). 4536–4551. 4 indexed citations
4.
Mao, Yimin, et al.. (2024). Predicting the elasticity modulus of sedimentary rocks using Deep Random Forest Optimization (DRFO) algorithm. Environmental Earth Sciences. 83(16). 14 indexed citations
5.
Mao, Yimin, et al.. (2024). Utilizing Hybrid Machine Learning and Soft Computing Techniques for Landslide Susceptibility Mapping in a Drainage Basin. Water. 16(3). 380–380. 55 indexed citations breakdown →
6.
Mwakapesa, Deborah Simon, et al.. (2024). Landslide susceptibility assessment using deep learning considering unbalanced samples distribution. Heliyon. 10(9). e30107–e30107. 8 indexed citations
7.
Deng, Xueyang, et al.. (2023). Deep Convolutional Neural Network Algorithm Based on Im2Col and Non-Local Mean Filter. 6. 6–10. 2 indexed citations
8.
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10.
Mwakapesa, Deborah Simon, et al.. (2023). Landslide susceptibility mapping using O-CURE and PAM clustering algorithms. Frontiers in Environmental Science. 11. 6 indexed citations
11.
Mao, Yimin, et al.. (2023). Azarshahr travertine compression strength prediction based on point-load index (Is) data using multilayer perceptron. Scientific Reports. 13(1). 20807–20807. 4 indexed citations
12.
Mao, Yimin, et al.. (2021). Innovative Landslide Susceptibility Mapping Portrayed by CA‐AQD and K‐Means Clustering Algorithms. Advances in Civil Engineering. 2021(1). 17 indexed citations
13.
Mao, Yimin, et al.. (2021). Landslide susceptibility modelling based on AHC-OLID clustering algorithm. Advances in Space Research. 68(1). 301–316. 20 indexed citations
14.
Mao, Yimin, et al.. (2021). Assessment of landslide susceptibility using DBSCAN-AHD and LD-EV methods. Journal of Mountain Science. 19(1). 184–197. 13 indexed citations
15.
Liu, Xiangmin, Jian Hu, Deborah Simon Mwakapesa, et al.. (2021). A novel MapReduce-based deep convolutional neural network algorithm. Journal of Intelligent & Fuzzy Systems. 41(2). 2603–2615. 4 indexed citations
16.
Mao, Yimin & Yinping Liu. (2020). Functional Module Mining in Uncertain PPI Network Based on Fuzzy Spectral Clustering. 91–106. 1 indexed citations
17.
Hu, Jian, et al.. (2019). Using Uncertain DM-Chameleon Clustering Algorithm Based on Machine Learning to Predict Landslide Hazards. Journal of Robotics and Mechatronics. 31(2). 329–338. 7 indexed citations
18.
Gao, Xiaodong, et al.. (2017). Research and application of an uncertain genetic neural network in landslide hazard prediction. 7(3). 140–140. 2 indexed citations
19.
Mao, Yimin, et al.. (2017). The essential and downstream common proteins of amyotrophic lateral sclerosis: A protein-protein interaction network analysis. PLoS ONE. 12(3). e0172246–e0172246. 12 indexed citations
20.
Mao, Yimin, et al.. (2017). Landslide susceptibility assessment using uncertain decision tree model in loess areas. Environmental Earth Sciences. 76(22). 22 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.

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