Jui-Yu Wu

402 total citations
26 papers, 268 citations indexed

About

Jui-Yu Wu is a scholar working on Artificial Intelligence, Biomedical Engineering and Signal Processing. According to data from OpenAlex, Jui-Yu Wu has authored 26 papers receiving a total of 268 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 8 papers in Biomedical Engineering and 7 papers in Signal Processing. Recurrent topics in Jui-Yu Wu's work include Metaheuristic Optimization Algorithms Research (13 papers), Neural Networks and Applications (12 papers) and Artificial Immune Systems Applications (7 papers). Jui-Yu Wu is often cited by papers focused on Metaheuristic Optimization Algorithms Research (13 papers), Neural Networks and Applications (12 papers) and Artificial Immune Systems Applications (7 papers). Jui-Yu Wu collaborates with scholars based in Taiwan, China and United States. Jui-Yu Wu's co-authors include Chi-Jie Lu, Enrique J. Lavernia, Tian‐Shyug Lee and Chih‐Chou Chiu and has published in prestigious journals such as Expert Systems with Applications, Applied Soft Computing and The Scientific World JOURNAL.

In The Last Decade

Jui-Yu Wu

25 papers receiving 254 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jui-Yu Wu Taiwan 9 121 106 55 46 28 26 268
Claus Aranha Japan 10 102 0.8× 174 1.6× 29 0.5× 31 0.7× 23 0.8× 37 337
Sudarsan Padhy India 10 120 1.0× 85 0.8× 76 1.4× 46 1.0× 17 0.6× 18 287
Renzhong Wang United States 9 121 1.0× 53 0.5× 32 0.6× 48 1.0× 103 3.7× 26 300
Leon Wu United States 11 42 0.3× 48 0.5× 97 1.8× 18 0.4× 37 1.3× 23 316
Eva Alfaro-Cid Spain 11 51 0.4× 84 0.8× 28 0.5× 29 0.6× 93 3.3× 24 260
Mariam Kiran United States 11 25 0.2× 86 0.8× 95 1.7× 11 0.2× 40 1.4× 47 396
Mehmet Anıl Akbay Türkiye 6 151 1.2× 51 0.5× 46 0.8× 39 0.8× 24 0.9× 8 249
Sashank Sridhar India 10 66 0.5× 94 0.9× 38 0.7× 17 0.4× 10 0.4× 54 280
Siqi Tang China 7 126 1.0× 34 0.3× 84 1.5× 39 0.8× 7 0.3× 12 253

Countries citing papers authored by Jui-Yu Wu

Since Specialization
Citations

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

Fields of papers citing papers by Jui-Yu Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jui-Yu Wu. 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 Jui-Yu Wu. The network helps show where Jui-Yu Wu may publish in the future.

Co-authorship network of co-authors of Jui-Yu Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Jui-Yu Wu. A scholar is included among the top collaborators of Jui-Yu Wu 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 Jui-Yu Wu. Jui-Yu Wu 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
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Wu, Jui-Yu, et al.. (2014). Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting. The Scientific World JOURNAL. 2014. 1–9. 2 indexed citations
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Wu, Jui-Yu. (2013). Solving Unconstrained Global Optimization Problems via Hybrid Swarm Intelligence Approaches. Mathematical Problems in Engineering. 2013. 1–15. 10 indexed citations
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Wu, Jui-Yu. (2012). Solving Constrained Global Optimization Problems by Using Hybrid Evolutionary Computing and Artificial Life Approaches. Mathematical Problems in Engineering. 2012(1). 6 indexed citations
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Lu, Chi-Jie & Jui-Yu Wu. (2011). An efficient CMAC neural network for stock index forecasting. Expert Systems with Applications. 38(12). 15194–15201. 30 indexed citations
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Wu, Jui-Yu, et al.. (2011). Combining nonlinear independent component analysis and neural network for the prediction of Asian stock market indexes. Expert Systems with Applications. 39(4). 4444–4452. 85 indexed citations
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Wu, Jui-Yu. (2010). MIMO CMAC neural network classifier for solving classification problems. Applied Soft Computing. 11(2). 2326–2333. 14 indexed citations
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Wu, Jui-Yu. (2010). Advanced simulated annealing-based BPNN for forecasting chaotic time series. 220. V1–38. 7 indexed citations
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Wu, Jui-Yu, et al.. (2009). Combining ICA and SVR in Times Series Predication. 1128–1132. 1 indexed citations
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Lu, Chi-Jie, et al.. (2009). Forecasting stock price using Nonlinear independent component analysis and support vector regression. 4. 2370–2374. 4 indexed citations
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Wu, Jui-Yu & Chi-Jie Lu. (2009). Neuro-computing Method for Data Mining. 184–188. 1 indexed citations
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Lu, Chi-Jie, Jui-Yu Wu, & Tian‐Shyug Lee. (2009). Application of Independent Component Analysis Preprocessing and Support Vector Regression in Time Series Prediction. 468–471. 5 indexed citations
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Wu, Jui-Yu, et al.. (2007). Real-Coded Genetic Algorithm for Solving Generalized Polynomial Programming Problems. Journal of Advanced Computational Intelligence and Intelligent Informatics. 11(4). 358–364. 8 indexed citations
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Wu, Jui-Yu, et al.. (1993). Coarsening behavior of primary Si in melt-spun Al-22 wt. % Si. Scripta Metallurgica et Materialia. 29(1). 31–36. 20 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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