Takashi Maeda

505 citations
11 papers · 347 indexed · h-index 8
Topics
Optimization and Variational Analysis (7 papers)Fuzzy Systems and Optimization (5 papers)Advanced Optimization Algorithms Research (4 papers)
Partner nations
Japan

In The Last Decade

Takashi Maeda

10 papers receiving 328 citations

Peers

Takashi Maeda
Comparison fields: 5 of 44
  • Computational Theory and Mathematics 192
  • Management Science and Operations Research 162
  • Statistics and Probability 130
  • Numerical Analysis 128
  • Control and Systems Engineering 94
Replace Norbert Gaffke with:
Norbert Gaffke Germany
Shu Lü United States
Anurag Jayswal India
Chin-Tzong Pang Taiwan
Ebrahim A. Youness Egypt
Shuwen Xiang China
Elisabeth Köbis Germany
Tamaki Tanaka Japan
Andreas Löhne Germany
Laura Martein Italy
Takashi Maeda relative to Norbert Gaffke Germany Norbert Gaffke's profile →
Citations per field
00.5×3.4×
Norbert Gaffke · 1×
Citations per year

Countries citing papers authored by Takashi Maeda

Since Specialization
Citations

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

Fields of papers citing papers by Takashi Maeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Takashi Maeda

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

All Works

11 of 11 papers shown
#WorkIndexed citations
1 20
2 4
3 0
4 9
5
On Characterization of Nash Equilibrium Strategy of Bi-matrix Games with Fuzzy Payoffs(Mathematical Economics)
1
6 29
7 14
8 82
9 15
10 66
11 107

About Takashi Maeda

Takashi Maeda is a scholar working on Numerical Analysis, Statistics and Probability and Computational Theory and Mathematics, having authored 11 papers that have together received 347 indexed citations. Recurring topics across this work include Optimization and Variational Analysis (7 papers), Fuzzy Systems and Optimization (5 papers) and Advanced Optimization Algorithms Research (4 papers). The work is most often cited by research in Numerical Analysis (128 citations), Statistics and Probability (130 citations) and Management Science and Operations Research (162 citations). Takashi Maeda has collaborated with scholars based in Japan. Frequent co-authors include Goutam Chakraborty and Basabi Chakraborty. Their work appears in journals such as Fuzzy Sets and Systems, Journal of Mathematical Analysis and Applications and Applied Mathematics and Computation.

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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