Tomoo Aoyama

624 total citations
42 papers, 482 citations indexed

About

Tomoo Aoyama is a scholar working on Computational Theory and Mathematics, Spectroscopy and Artificial Intelligence. According to data from OpenAlex, Tomoo Aoyama has authored 42 papers receiving a total of 482 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computational Theory and Mathematics, 8 papers in Spectroscopy and 6 papers in Artificial Intelligence. Recurrent topics in Tomoo Aoyama's work include Computational Drug Discovery Methods (7 papers), Analytical Chemistry and Chromatography (5 papers) and Neural Networks and Applications (5 papers). Tomoo Aoyama is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Analytical Chemistry and Chromatography (5 papers) and Neural Networks and Applications (5 papers). Tomoo Aoyama collaborates with scholars based in Japan, China and South Korea. Tomoo Aoyama's co-authors include Hiroshi Ichikawa, Yuji Suzuki, Hiroshi Ichikawa, Umpei Nagashima, Yuji Suzuki, Ichiro Shima, Naoki Inamoto, Masaaki Yoshifuji, Haruo Hosoya and Aiko Yamauchi and has published in prestigious journals such as Journal of Medicinal Chemistry, Chemical Physics Letters and Journal of Computational Chemistry.

In The Last Decade

Tomoo Aoyama

31 papers receiving 410 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tomoo Aoyama Japan 9 264 142 114 102 78 42 482
Lu Xu China 12 355 1.3× 212 1.5× 123 1.1× 82 0.8× 161 2.1× 52 650
B. T. Fan China 8 187 0.7× 106 0.7× 110 1.0× 65 0.6× 56 0.7× 16 342
Anil Kumar Pandey India 7 396 1.5× 72 0.5× 217 1.9× 50 0.5× 74 0.9× 19 591
Sían Howells United Kingdom 12 116 0.4× 133 0.9× 170 1.5× 84 0.8× 87 1.1× 17 484
Iiris Kahn Estonia 7 337 1.3× 110 0.8× 109 1.0× 47 0.5× 172 2.2× 12 675
K. Kollár‐Hunek Hungary 7 133 0.5× 88 0.6× 66 0.6× 102 1.0× 43 0.6× 8 398
Yoshikatsu Miyashita Japan 16 279 1.1× 208 1.5× 160 1.4× 185 1.8× 200 2.6× 39 740
M. I. S. Sastry India 11 182 0.7× 79 0.6× 200 1.8× 63 0.6× 75 1.0× 25 590
Aboozar Khajeh Iran 14 126 0.5× 89 0.6× 107 0.9× 48 0.5× 106 1.4× 28 694
Adam Fedorowicz United States 14 136 0.5× 75 0.5× 215 1.9× 21 0.2× 63 0.8× 22 628

Countries citing papers authored by Tomoo Aoyama

Since Specialization
Citations

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

Fields of papers citing papers by Tomoo Aoyama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomoo Aoyama

This figure shows the co-authorship network connecting the top 25 collaborators of Tomoo Aoyama. A scholar is included among the top collaborators of Tomoo Aoyama 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 Tomoo Aoyama. Tomoo Aoyama 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.
Nagashima, Umpei, et al.. (2013). A Function of Residence Half-life of Radioisotope Substances. Journal of Computer Chemistry Japan. 12(2). 122–132.
2.
Aoyama, Tomoo, et al.. (2012). Residence Half-life of Radioisotope Substances. Journal of Computer Chemistry Japan. 11(1). 49–77. 1 indexed citations
3.
Aoyama, Tomoo, et al.. (2011). Consideration of Diffusion of Radioisotope Dust. Journal of Computer Chemistry Japan. 10(2). A7–A12. 2 indexed citations
4.
Aoyama, Tomoo, et al.. (2010). A Photographic Approach for Visualization of Suspended Particulate Matter: Data Processing of RAW Format. Journal of Computer Chemistry Japan. 9(5). 219–230. 1 indexed citations
5.
Aoyama, Tomoo, et al.. (2009). A Photographic Approach for Visualization of Suspended Particulate Matter. Journal of Computer Chemistry Japan. 8(1). 13–22. 5 indexed citations
6.
Aoyama, Tomoo, et al.. (2009). Relations between the Sky Hue and Aerosol Scattering. Journal of Computer Chemistry Japan. 8(4). 153–164. 3 indexed citations
7.
Aoyama, Tomoo, et al.. (2007). Analysis of the Water Quality of the Yoshinogawa, Tokushima, Japan, by Using Multivariate Analysis. Journal of Computer Chemistry Japan. 6(1). 1–18. 2 indexed citations
8.
Aoyama, Tomoo, et al.. (2007). Development of Neural Network for Incomplete Data Set, CQSAR: Compensation Quantitative Structure-Activity Relationships. Journal of Computer Chemistry Japan. 6(5). 263–274.
9.
Aoyama, Tomoo, et al.. (2006). An Approach to Plant Identification Technology. 제어로봇시스템학회 국제학술대회 논문집. 5478–5483. 5 indexed citations
10.
Aoyama, Tomoo, et al.. (2005). Comparison with Water Quality of main Rivers in the world, based on OECD reports. 제어로봇시스템학회 국제학술대회 논문집. 935–940. 1 indexed citations
11.
Aoyama, Tomoo, et al.. (2005). Development of a Simplified Eddy Current Tester Specialized in Non-Iron Metals. 제어로봇시스템학회 국제학술대회 논문집. 805–808. 3 indexed citations
12.
Yan, Yuan, et al.. (2003). A new learning algorithm for incomplete data sets and multi-layer neural networks. 제어로봇시스템학회 국제학술대회 논문집. 150–155. 2 indexed citations
13.
Yuan, Yan, et al.. (2003). Applications of artificial neural networks. 제어로봇시스템학회 국제학술대회 논문집. 1036–1041. 3 indexed citations
14.
Aoyama, Tomoo, et al.. (2001). Inverse optimization problem solver on use of multi-layer neural networks. 제어로봇시스템학회 국제학술대회 논문집. 587–590.
15.
Aoyama, Tomoo, et al.. (2001). A neural network solver for differential equations. 제어로봇시스템학회 국제학술대회 논문집. 583–586. 2 indexed citations
16.
Aoyama, Tomoo, et al.. (2000). Learning-possibility for neuron model in Medical Superior Temporal area. 제어로봇시스템학회 국내학술대회 논문집. 2. 516–516. 5 indexed citations
17.
Yoshihara, Ikuo, et al.. (1999). Prediction of Time Histories of Seismic Ground Motion Using Genetic Programming. 제어로봇시스템학회 국내학술대회 논문집. 5. 226–229. 1 indexed citations
18.
Aoyama, Tomoo, et al.. (1999). Functional memories constructed of neural network. 제어로봇시스템학회 국내학술대회 논문집. 5. 210–213. 1 indexed citations
19.
Aoyama, Tomoo, et al.. (1999). Forecasting and precision on using multi-layer neural network. 5(81). 218–221. 1 indexed citations
20.
Nagashima, Umpei, et al.. (1998). Neural Network Reproduction of Time Series Data with Varying Amplitudes and Frequencies.. 4(2). 57–72. 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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