Tong‐Seng Quah

516 citations
19 papers · 368 indexed · h-index 8
Topics
Neural Networks and Applications (11 papers)Software Engineering Research (7 papers)Stock Market Forecasting Methods (7 papers)
Partner nations
Singapore

In The Last Decade

Tong‐Seng Quah

16 papers receiving 323 citations

Peers

Tong‐Seng Quah
Comparison fields: 5 of 38
  • Information Systems 181
  • Software 160
  • Management Science and Operations Research 138
  • Artificial Intelligence 97
  • Computer Networks and Communications 69
Replace Sebastian Ng with:
Sebastian Ng Australia
Roy S. Freedman United States
Xuelin Li United States
Paulius Danėnas Lithuania
Ching-Seh Wu United States
Jairus Hihn United States
Biju R. Mohan India
Cliff T. Ragsdale United States
Gernot Salzer Austria
Jarley P. Nóbrega Brazil
Tong‐Seng Quah relative to Sebastian Ng Australia Sebastian Ng's profile →
Citations per field
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Sebastian Ng · 1×
Citations per year

Countries citing papers authored by Tong‐Seng Quah

Since Specialization
Citations

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

Fields of papers citing papers by Tong‐Seng Quah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tong‐Seng Quah. 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 Tong‐Seng Quah. The network helps show where Tong‐Seng Quah may publish in the future.

Co-authorship network of co-authors of Tong‐Seng Quah

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

All Works

19 of 19 papers shown
#WorkIndexed citations
1 21
2
Using Neural Network for DJIA Stock Selection
7
3 37
4 2
5 1
6 0
7 0
8 96
9 12
10
Application of Neural Networks for Estimating Software Maintainability Using Object-Oriented Metrics.
7
11 21
12 25
13 1
14
Segmental Stock Market Prediction Using Neural Network.
1
15 105
16 21
17 4
18 4
19 3

About Tong‐Seng Quah

Tong‐Seng Quah is a scholar working on Software, Management Science and Operations Research and Artificial Intelligence, having authored 19 papers that have together received 368 indexed citations. Recurring topics across this work include Neural Networks and Applications (11 papers), Software Engineering Research (7 papers) and Stock Market Forecasting Methods (7 papers). The work is most often cited by research in Software (160 citations), Management Science and Operations Research (138 citations) and Information Systems (181 citations). Tong‐Seng Quah has collaborated with scholars based in Singapore. Frequent co-authors include Chew‐Lim Tan, C.L. Tan, Chew-Lim Tan and Melvin Lee. Their work appears in journals such as Expert Systems with Applications, Information Sciences and Decision Support Systems.

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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