Hong Men

1.1k total citations
62 papers, 834 citations indexed

About

Hong Men is a scholar working on Biomedical Engineering, Sensory Systems and Nutrition and Dietetics. According to data from OpenAlex, Hong Men has authored 62 papers receiving a total of 834 indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Biomedical Engineering, 16 papers in Sensory Systems and 15 papers in Nutrition and Dietetics. Recurrent topics in Hong Men's work include Advanced Chemical Sensor Technologies (44 papers), Olfactory and Sensory Function Studies (16 papers) and Biochemical Analysis and Sensing Techniques (15 papers). Hong Men is often cited by papers focused on Advanced Chemical Sensor Technologies (44 papers), Olfactory and Sensory Function Studies (16 papers) and Biochemical Analysis and Sensing Techniques (15 papers). Hong Men collaborates with scholars based in China, Vietnam and South Korea. Hong Men's co-authors include Yan Shi, Jingjing Liu, Mei Liu, Chongbo Yin, Qinglun Zhang, Mingyang Wang, Shuyue Jia, Ziyang Li, Haoming Chen and Qi Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Food Chemistry and Expert Systems with Applications.

In The Last Decade

Hong Men

58 papers receiving 818 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hong Men China	16	617	246	174	150	131	62	834
Yan Shi China	23	847 1.4×	378 1.5×	354 2.0×	189 1.3×	160 1.2×	93	1.5k
Manabendra Bhuyan India	16	814 1.3×	324 1.3×	206 1.2×	113 0.8×	83 0.6×	67	1.2k
Arun Jana India	14	906 1.5×	362 1.5×	207 1.2×	169 1.1×	127 1.0×	22	1.1k
Noureddine El Barbri Morocco	13	566 0.9×	200 0.8×	159 0.9×	116 0.8×	62 0.5×	33	683
Hamed Karami Iran	23	762 1.2×	429 1.7×	193 1.1×	153 1.0×	69 0.5×	63	1.4k
Huichun Yu China	20	599 1.0×	433 1.8×	128 0.7×	147 1.0×	42 0.3×	47	1.1k
Aziz Amari Morocco	10	445 0.7×	121 0.5×	174 1.0×	66 0.4×	43 0.3×	21	565
Miguel Peris Spain	14	957 1.6×	257 1.0×	212 1.2×	139 0.9×	124 0.9×	30	1.3k
Juan Manuel Gutiérrez Mexico	20	817 1.3×	143 0.6×	346 2.0×	84 0.6×	83 0.6×	55	1.2k
Xuezhen Hong China	12	366 0.6×	214 0.9×	72 0.4×	59 0.4×	33 0.3×	16	611

Countries citing papers authored by Hong Men

Since Specialization

Citations

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

Fields of papers citing papers by Hong Men

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hong Men

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Zhang, Qinglun, et al.. (2026). Temporal feature mixed inverted transformer: An inverted transformer for effective real-time electricity price forecasting. Engineering Applications of Artificial Intelligence. 167. 113778–113778.

Liu, Chenrui, et al.. (2025). Optimizing Food Taste Sensory Evaluation Through Neural Network-Based Taste Electroencephalogram Channel Selection. IEEE Transactions on Instrumentation and Measurement. 74. 1–9. 2 indexed citations

Wang, Baichun, et al.. (2025). TVNet: A times vision network for electrical load forecasting by temporal 2d-variation. Expert Systems with Applications. 280. 127619–127619.

Liu, Chenrui, et al.. (2025). Cross-individual electrophysiological signal recognition in Clivia biosensors via domain adaptation. Applied Soft Computing. 178. 113323–113323.

Shi, Yan, et al.. (2025). Origin traceability of agricultural products: A lightweight collaborative neural network for spectral information processing. Food Research International. 208. 116131–116131. 2 indexed citations

Yin, Chongbo, et al.. (2025). Gas Features Cooperative Calculation Neural Network Combined With an Electronic Nose System for Peanut Origin Identification. IEEE Transactions on Instrumentation and Measurement. 74. 1–9.

Guo, Yuchen, et al.. (2024). Olfactory EEG induced by odor: Used for food identification and pleasure analysis. Food Chemistry. 455. 139816–139816. 6 indexed citations

Zhang, Z.G., et al.. (2024). Advancing research on odor-induced sweetness enhancement: A EEG local-global fusion transformer network for sweetness quantification combined with EEG technology. Food Chemistry. 463(Pt 4). 141533–141533. 14 indexed citations

Wang, Yanwei, Qinghua Li, Chongbo Yin, et al.. (2024). A gas detection system combined with a global extension extreme learning machine for early warning of electrical fires. Sensors and Actuators B Chemical. 423. 136801–136801. 9 indexed citations

10.

Men, Hong, et al.. (2023). Image registration based fault localization in panoramas of mountain-mounted PV plants. Solar Energy. 256. 16–31. 8 indexed citations

11.

Shi, Yan, et al.. (2023). FBANet: An Effective Data Mining Method for Food Olfactory EEG Recognition. IEEE Transactions on Neural Networks and Learning Systems. 35(10). 13550–13560. 22 indexed citations

12.

Wang, Bo, et al.. (2023). Recognition of odor and pleasantness based on olfactory EEG combined with functional brain network model. International Journal of Machine Learning and Cybernetics. 14(8). 2761–2776. 11 indexed citations

13.

Liu, Jingjing, et al.. (2020). Detection of Apple Taste Information Using Model Based on Hyperspectral Imaging and Electronic Tongue Data. Sensors and Materials. 32(5). 1767–1767. 7 indexed citations

14.

Shi, Yan, et al.. (2020). Origin traceability of rice based on an electronic nose coupled with a feature reduction strategy. Measurement Science and Technology. 32(2). 25107–25107. 24 indexed citations

15.

Liu, Jingjing, et al.. (2016). Automatic Evaluation of Sensory Information for Beer at a Fuzzy Level Using Electronic Tongue and Electronic Nose. Sensors and Materials. 785–785. 10 indexed citations

16.

Men, Hong, et al.. (2014). Fuzzy ARTMAP for the Adulterated Honey Discrimination with Voltammetric Electronic Tongue. SHILAP Revista de lepidopterología. 4 indexed citations

17.

Men, Hong, et al.. (2013). Microbial Growth Modeling and Simulation Based on Cellular Automata. Research Journal of Applied Sciences Engineering and Technology. 6(11). 2061–2066. 2 indexed citations

18.

Men, Hong, et al.. (2013). Application of Electronic Tongue in Edible Oil Detection with Cluster Algorithm based on Artificial Fish Swarm Improvement. Advance Journal of Food Science and Technology. 5(4). 469–473. 7 indexed citations

19.

Men, Hong, et al.. (2013). Study on Iron Bacteria Induced Corrosion Based on Electrochemical Noise and RBF Neural Network. Research Journal of Applied Sciences Engineering and Technology. 6(7). 1309–1315. 1 indexed citations

20.

Men, Hong, et al.. (2012). An Electronic Tongue Based on Differential Pulse Voltammetry and Its Application in the Classification of Green Tea. Advanced Science Letters. 11(1). 189–193. 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.

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