Shingo Mabu

3.0k total citations
310 papers, 2.1k citations indexed

About

Shingo Mabu is a scholar working on Artificial Intelligence, Control and Systems Engineering and Management Science and Operations Research. According to data from OpenAlex, Shingo Mabu has authored 310 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 206 papers in Artificial Intelligence, 71 papers in Control and Systems Engineering and 52 papers in Management Science and Operations Research. Recurrent topics in Shingo Mabu's work include Evolutionary Algorithms and Applications (142 papers), Metaheuristic Optimization Algorithms Research (114 papers) and Elevator Systems and Control (51 papers). Shingo Mabu is often cited by papers focused on Evolutionary Algorithms and Applications (142 papers), Metaheuristic Optimization Algorithms Research (114 papers) and Elevator Systems and Control (51 papers). Shingo Mabu collaborates with scholars based in Japan, China and Indonesia. Shingo Mabu's co-authors include Kotaro Hirasawa, Kaoru Shimada, Jinglu Hu, Takashi Kuremoto, Masanao Obayashi, Kotaro Hirasawa, Xianneng Li, Ci Chen, Yan Chen and Nannan Lu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Shingo Mabu

274 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shingo Mabu Japan 22 1.2k 450 343 270 254 310 2.1k
Masri Ayob Malaysia 25 976 0.8× 557 1.2× 157 0.5× 133 0.5× 235 0.9× 123 2.2k
Ahamad Tajudin Khader Malaysia 27 756 0.6× 352 0.8× 328 1.0× 135 0.5× 182 0.7× 65 2.1k
Detlef Nauck United Kingdom 20 1.5k 1.2× 227 0.5× 320 0.9× 168 0.6× 151 0.6× 66 2.3k
Shie-Jue Lee Taiwan 21 1.0k 0.9× 333 0.7× 197 0.6× 193 0.7× 206 0.8× 120 1.8k
Jinglu Hu Japan 22 1.5k 1.3× 277 0.6× 588 1.7× 148 0.5× 167 0.7× 294 2.6k
Yinan Guo China 25 1.2k 1.0× 180 0.4× 298 0.9× 48 0.2× 120 0.5× 110 2.1k
Ran Wang China 28 1.5k 1.2× 234 0.5× 177 0.5× 200 0.7× 134 0.5× 88 2.4k
José M. Puerta Spain 19 819 0.7× 148 0.3× 81 0.2× 135 0.5× 85 0.3× 75 1.4k
Zne-Jung Lee Taiwan 20 973 0.8× 93 0.2× 289 0.8× 153 0.6× 317 1.2× 73 2.1k
Rafael Alcalá Spain 25 2.3k 1.9× 384 0.9× 308 0.9× 95 0.4× 95 0.4× 71 2.9k

Countries citing papers authored by Shingo Mabu

Since Specialization
Citations

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

Fields of papers citing papers by Shingo Mabu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shingo Mabu

This figure shows the co-authorship network connecting the top 25 collaborators of Shingo Mabu. A scholar is included among the top collaborators of Shingo Mabu 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 Shingo Mabu. Shingo Mabu 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.
Mabu, Shingo, et al.. (2023). Improved artificial intelligence discrimination of minor histological populations by supplementing with color-adjusted images. Scientific Reports. 13(1). 19068–19068. 2 indexed citations
2.
Mabu, Shingo, et al.. (2012). Two-Stage Reinforcement Learning based on Genetic Network Programming for mobile robot. Society of Instrument and Control Engineers of Japan. 95–100. 1 indexed citations
3.
Mabu, Shingo, et al.. (2011). A novel intrusion detection system based on the 2-dimensional space distribution of average matching degree. Society of Instrument and Control Engineers of Japan. 2829–2834. 3 indexed citations
4.
Mabu, Shingo, et al.. (2011). Trading rules on stock markets using Genetic Network Programming-Sarsa Learning with plural subroutines. Society of Instrument and Control Engineers of Japan. 143–148. 1 indexed citations
5.
Zhang, Deng, Shingo Mabu, & Kotaro Hirasawa. (2011). A robust intelligent face recognition framework using GNP-based multi-agent system. Society of Instrument and Control Engineers of Japan. 1152–1156. 2 indexed citations
6.
Mabu, Shingo, et al.. (2011). Pruning high-level network using genetic algorithm for efficient hierarchical route planning in road networks. Society of Instrument and Control Engineers of Japan. 2903–2909. 2 indexed citations
7.
Wang, Lutao, et al.. (2010). Generalized rule accumulation based on Genetic Network Programming considering different population size and rule length. Society of Instrument and Control Engineers of Japan. 2631–2636.
8.
Mabu, Shingo, et al.. (2010). Automatic program generation with genetic network programming using subroutines. Society of Instrument and Control Engineers of Japan. 3089–3094. 2 indexed citations
11.
Mabu, Shingo, et al.. (2010). Web mining using Genetic Relation Algorithm. Society of Instrument and Control Engineers of Japan. 1622–1627. 4 indexed citations
12.
Li, Jianhua, et al.. (2010). Trading rules on stock markets using genetic network programming with subroutines. Society of Instrument and Control Engineers of Japan. 3084–3088. 2 indexed citations
13.
Mabu, Shingo, et al.. (2010). Generating stock trading signals based on matching degree with extracted rules by genetic network programming. Society of Instrument and Control Engineers of Japan. 1164–1169. 2 indexed citations
14.
Chen, Ci, et al.. (2009). Analysis of fuzzy class association rule mining based on Genetic Network Programming. 2009 ICCAS-SICE. 3480–3484. 2 indexed citations
15.
Yu, Shanqing, et al.. (2009). Temperature parameter control of Q value-based Dynamic Programming with Boltzmann distribution. 2009 ICCAS-SICE. 1471–1476.
16.
Yang, Guangfei, Shingo Mabu, Kaoru Shimada, & Kotaro Hirasawa. (2009). A new associative classification method by integrating CMAR and an evolutionary three-layers structure. 2009 ICCAS-SICE. 2920–2925. 1 indexed citations
17.
Mabu, Shingo, et al.. (2009). Class association rule mining with correlation measures using genetic network programming. 2009 ICCAS-SICE. 3850–3856. 1 indexed citations
18.
Li, Xianneng, Shingo Mabu, Huiyu Zhou, Kaoru Shimada, & Kotaro Hirasawa. (2009). Genetic Network Programming with Estimation of Distribution Algorithms and its application to association rule mining for traffic prediction. 2009 ICCAS-SICE. 3457–3462. 13 indexed citations
19.
Mabu, Shingo, et al.. (2009). Fuzzy association rule mining and classifier with chi-squared correlation measure using genetic network programming. 2009 ICCAS-SICE. 3863–3869. 1 indexed citations
20.
Yue, Chuan, et al.. (2009). Agent bidding strategy of multiple round English Auction based on genetic network programming. 2009 ICCAS-SICE. 3857–3862. 7 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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