Shin‐Li Lu

452 total citations
40 papers, 381 citations indexed

About

Shin‐Li Lu is a scholar working on Statistics, Probability and Uncertainty, Management Science and Operations Research and Statistics and Probability. According to data from OpenAlex, Shin‐Li Lu has authored 40 papers receiving a total of 381 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Statistics, Probability and Uncertainty, 14 papers in Management Science and Operations Research and 14 papers in Statistics and Probability. Recurrent topics in Shin‐Li Lu's work include Advanced Statistical Process Monitoring (26 papers), Scientific Measurement and Uncertainty Evaluation (19 papers) and Advanced Statistical Methods and Models (14 papers). Shin‐Li Lu is often cited by papers focused on Advanced Statistical Process Monitoring (26 papers), Scientific Measurement and Uncertainty Evaluation (19 papers) and Advanced Statistical Methods and Models (14 papers). Shin‐Li Lu collaborates with scholars based in Taiwan, United Kingdom and United States. Shin‐Li Lu's co-authors include Shey‐Huei Sheu, Chen‐Fang Tsai, W. K. Chiu, Su‐Fen Yang, Barry C. Arnold, Nazaraf Shah, Kuo‐Ming Chao and Chen Yanchun and has published in prestigious journals such as Expert Systems with Applications, Renewable Energy and Applied Sciences.

In The Last Decade

Shin‐Li Lu

40 papers receiving 371 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shin‐Li Lu Taiwan 12 282 190 88 45 41 40 381
Ali Hussein AL-Marshadi Saudi Arabia 11 228 0.8× 160 0.8× 92 1.0× 48 1.1× 15 0.4× 42 321
Osama H. Arif Saudi Arabia 13 344 1.2× 333 1.8× 119 1.4× 71 1.6× 5 0.1× 31 488
Shovan Chowdhury India 10 205 0.7× 232 1.2× 82 0.9× 22 0.5× 7 0.2× 31 370
Sandile Charles Shongwe South Africa 14 458 1.6× 269 1.4× 74 0.8× 149 3.3× 5 0.1× 69 541
Michael Jong Kim Canada 11 113 0.4× 55 0.3× 86 1.0× 78 1.7× 17 0.4× 23 337
Chau‐Chen Torng Taiwan 12 281 1.0× 126 0.7× 78 0.9× 55 1.2× 8 0.2× 23 358
F. G. Badía Spain 11 159 0.6× 280 1.5× 74 0.8× 24 0.5× 6 0.1× 45 491
T. C. Chang Singapore 11 285 1.0× 145 0.8× 28 0.3× 70 1.6× 7 0.2× 16 336
Shabbir Ahmad Pakistan 19 776 2.8× 540 2.8× 67 0.8× 255 5.7× 5 0.1× 38 888
Weiyong Ding China 12 173 0.6× 231 1.2× 35 0.4× 47 1.0× 27 0.7× 29 327

Countries citing papers authored by Shin‐Li Lu

Since Specialization
Citations

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

Fields of papers citing papers by Shin‐Li Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shin‐Li Lu. 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 Shin‐Li Lu. The network helps show where Shin‐Li Lu may publish in the future.

Co-authorship network of co-authors of Shin‐Li Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Shin‐Li Lu. A scholar is included among the top collaborators of Shin‐Li Lu 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 Shin‐Li Lu. Shin‐Li Lu 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.
Lu, Shin‐Li, et al.. (2022). An enhanced sum of squares generally weighted moving average chart based on auxiliary information for process monitoring. Journal of Statistical Computation and Simulation. 93(1). 188–208. 1 indexed citations
2.
Lu, Shin‐Li, et al.. (2021). Auxiliary information‐based maximum generally weighted moving average chart for simultaneously monitoring process mean and variability. Quality and Reliability Engineering International. 37(8). 3242–3261. 7 indexed citations
3.
Lu, Shin‐Li, et al.. (2020). A New Sum of Squares Exponentially Weighted Moving Average Control Chart Using Auxiliary Information. Symmetry. 12(11). 1888–1888. 10 indexed citations
4.
Lu, Shin‐Li, et al.. (2019). Generally weighted moving average control charts using repetitive sampling. Communication in Statistics- Theory and Methods. 50(2). 297–310. 14 indexed citations
5.
Lu, Shin‐Li, et al.. (2019). Enhanced generally weighted moving average variance charts for monitoring process variance with individual observations. Quality and Reliability Engineering International. 36(1). 285–302. 11 indexed citations
6.
Lu, Shin‐Li, et al.. (2019). A nonparametric generally weighted moving average sign chart based on repetitive sampling. Communications in Statistics - Simulation and Computation. 51(3). 1137–1156. 15 indexed citations
7.
Lu, Shin‐Li. (2018). Integrating heuristic time series with modified grey forecasting for renewable energy in Taiwan. Renewable Energy. 133. 1436–1444. 43 indexed citations
8.
Lu, Shin‐Li. (2017). Non parametric double generally weighted moving average sign charts based on process proportion. Communication in Statistics- Theory and Methods. 47(11). 2684–2700. 18 indexed citations
9.
Sheu, Shey‐Huei, et al.. (2017). Forecasting the volatility of a combined multi‐country stock index using GWMA algorithms. Expert Systems. 35(3). 1 indexed citations
10.
Tsai, Chen‐Fang, et al.. (2016). DESIGN OF AN EXTENDED NONPARAMETRIC EWMA SIGN CHART. International journal of industrial engineering. 22(6). 2 indexed citations
11.
Lu, Shin‐Li, et al.. (2016). Statistically constrained economic design of maximum double EWMA control charts based on loss functions. Quality Technology & Quantitative Management. 14(3). 280–295. 17 indexed citations
12.
Lu, Shin‐Li. (2016). Applying fast initial response features on GWMA control charts for monitoring autocorrelation data. Communication in Statistics- Theory and Methods. 45(11). 3344–3356. 6 indexed citations
13.
Chiu, W. K. & Shin‐Li Lu. (2015). On the Steady-State Performance of the Poisson Double GWMA Control Chart. Quality Technology & Quantitative Management. 12(2). 195–208. 15 indexed citations
14.
Lu, Shin‐Li, et al.. (2015). Novel grey models for the trend forecast of Taiwan waste gas apparatus. International Journal of Environmental Technology and Management. 18(2). 170–170. 4 indexed citations
15.
Chao, Kuo‐Ming, Chen‐Fang Tsai, & Shin‐Li Lu. (2014). An intelligent GA-nonparametric DEWMA sign chart for green chain management. Pure (Coventry University). 28. 247–252. 2 indexed citations
16.
Lu, Shin‐Li, et al.. (2013). Considering Taguchi loss function on statistically constrained economic sum of squares exponentially weighted moving average charts. Journal of Statistical Computation and Simulation. 85(3). 572–586. 6 indexed citations
17.
Lu, Shin‐Li & Chen‐Fang Tsai. (2013). A Nonparametric GA-GWMA Sign Chart for Green SCM Optimization. 28. 504–508. 1 indexed citations
18.
Lu, Shin‐Li, et al.. (2013). Measuring the performance improvement of a double generally weighted moving average control chart. Expert Systems with Applications. 41(7). 3313–3322. 17 indexed citations
19.
Lu, Shin‐Li & W. K. Chiu. (2012). The Grey Forecasting Model on the Forecast of Green GDP Accounting in Taiwan. 1 indexed citations
20.
Sheu, Shey‐Huei & Shin‐Li Lu. (2008). MONITORING AUTOCORRELATED PROCESS MEAN AND VARIANCE USING A GWMA CHART BASED ON RESIDUALS. Asia Pacific Journal of Operational Research. 25(6). 781–792. 14 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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