Liang‐Ying Wei

1.1k total citations
27 papers, 825 citations indexed

About

Liang‐Ying Wei is a scholar working on Management Science and Operations Research, Artificial Intelligence and Economics and Econometrics. According to data from OpenAlex, Liang‐Ying Wei has authored 27 papers receiving a total of 825 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Management Science and Operations Research, 13 papers in Artificial Intelligence and 10 papers in Economics and Econometrics. Recurrent topics in Liang‐Ying Wei's work include Stock Market Forecasting Methods (16 papers), Neural Networks and Applications (9 papers) and Energy Load and Power Forecasting (9 papers). Liang‐Ying Wei is often cited by papers focused on Stock Market Forecasting Methods (16 papers), Neural Networks and Applications (9 papers) and Energy Load and Power Forecasting (9 papers). Liang‐Ying Wei collaborates with scholars based in Taiwan. Liang‐Ying Wei's co-authors include Ching‐Hsue Cheng, Tai-Liang Chen, Jing–Rong Chang, Jing-Wei Liu, You‐Shyang Chen, Jingwei Liu, Chien-Hsiun Chen, Jui-Fang Chang, Cheng-Lung Huang and Hao-En Chueh and has published in prestigious journals such as Expert Systems with Applications, Information Sciences and Neurocomputing.

In The Last Decade

Liang‐Ying Wei

27 papers receiving 782 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Liang‐Ying Wei Taiwan 11 571 270 251 233 115 27 825
Rui Neves Portugal 16 464 0.8× 265 1.0× 294 1.2× 237 1.0× 94 0.8× 46 1.1k
Chih-Sheng Lin Taiwan 5 596 1.0× 185 0.7× 356 1.4× 167 0.7× 87 0.8× 13 814
Rajashree Dash India 15 425 0.7× 148 0.5× 213 0.8× 456 2.0× 48 0.4× 52 921
Yakup Kara Türkiye 16 656 1.1× 291 1.1× 219 0.9× 186 0.8× 57 0.5× 27 1.4k
Arash Ghanbari Iran 10 364 0.6× 134 0.5× 213 0.8× 183 0.8× 45 0.4× 19 675
Erkam Güreşen Türkiye 3 508 0.9× 244 0.9× 245 1.0× 161 0.7× 62 0.5× 6 736
Priyank Thakkar India 8 939 1.6× 399 1.5× 383 1.5× 189 0.8× 107 0.9× 29 1.2k
Zhensong Chen China 12 311 0.5× 136 0.5× 175 0.7× 187 0.8× 49 0.4× 21 580
Saman Haratizadeh Iran 9 358 0.6× 128 0.5× 196 0.8× 137 0.6× 72 0.6× 18 574
S. Shahab Vietnam 6 351 0.6× 115 0.4× 189 0.8× 104 0.4× 53 0.5× 6 652

Countries citing papers authored by Liang‐Ying Wei

Since Specialization
Citations

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

Fields of papers citing papers by Liang‐Ying Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Liang‐Ying Wei. 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 Liang‐Ying Wei. The network helps show where Liang‐Ying Wei may publish in the future.

Co-authorship network of co-authors of Liang‐Ying Wei

This figure shows the co-authorship network connecting the top 25 collaborators of Liang‐Ying Wei. A scholar is included among the top collaborators of Liang‐Ying Wei 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 Liang‐Ying Wei. Liang‐Ying Wei 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.
Wei, Liang‐Ying, et al.. (2017). A Hybrid One-step-ahead Time Series Model Based on GA-SVR and EMD for Forecasting Electricity Loads. Journal of Applied Science and Engineering. 20(4). 467–476. 3 indexed citations
2.
Wei, Liang‐Ying, et al.. (2017). A hybrid time series model based on AR-EMD and volatility for medical data forecasting: A case study in the emergency department. Econstor (Econstor). 6. 166–184. 1 indexed citations
3.
Wei, Liang‐Ying. (2017). A Study of the Hybrid Recurrent Neural Network Model for Electricity Loads Forecasting. International Journal of Academic Research in Accounting Finance and Management Sciences. 7(2). 10 indexed citations
4.
Cheng, Ching‐Hsue & Liang‐Ying Wei. (2016). Rough Classifier Based on Region Growth Algorithm for Identifying Liver CT Image. Journal of Applied Science and Engineering. 19(1). 65–74. 3 indexed citations
5.
Wei, Liang‐Ying. (2016). A hybrid ANFIS model based on empirical mode decomposition for stock time series forecasting. Applied Soft Computing. 42. 368–376. 143 indexed citations
6.
Wei, Liang‐Ying. (2014). A Hybrid Model Based on ANFIS and Empirical Mode Decomposition for Stock Forecasting. Journal of Economics Business and Management. 3(3). 356–359. 5 indexed citations
7.
Cheng, Ching‐Hsue & Liang‐Ying Wei. (2013). A novel time-series model based on empirical mode decomposition for forecasting TAIEX. Economic Modelling. 36. 136–141. 71 indexed citations
8.
Wei, Liang‐Ying. (2012). AN ADAPTIVE EXPECTATION GENETIC ALGORITHM BASED ON ANFIS AND MULTINATIONAL STOCK MARKET VOLATILITY CAUSALITY FOR TAIEX FORECASTING. Cybernetics & Systems. 43(5). 410–425. 3 indexed citations
9.
Wei, Liang‐Ying. (2012). A GA-weighted ANFIS model based on multiple stock market volatility causality for TAIEX forecasting. Applied Soft Computing. 13(2). 911–920. 49 indexed citations
10.
Cheng, Ching‐Hsue, Liang‐Ying Wei, Jing-Wei Liu, & Tai-Liang Chen. (2012). OWA-based ANFIS model for TAIEX forecasting. Economic Modelling. 30. 442–448. 61 indexed citations
11.
Wei, Liang‐Ying. (2011). An expanded Adaptive Neuro-Fuzzy Inference System (ANFIS) model based on AR and causality of multi-nation stock market volatility for TAIEX forecasting. AFRICAN JOURNAL OF BUSINESS MANAGEMENT. 5(15). 6377–6387. 3 indexed citations
12.
Cheng, Ching‐Hsue, et al.. (2011). A NEW E‐LEARNING ACHIEVEMENT EVALUATION MODEL BASED ON ROUGH SET AND SIMILARITY FILTER. Computational Intelligence. 27(2). 260–279. 4 indexed citations
13.
Cheng, Ching‐Hsue, Tai-Liang Chen, & Liang‐Ying Wei. (2010). A hybrid model based on rough sets theory and genetic algorithms for stock price forecasting. Information Sciences. 180(9). 1610–1629. 154 indexed citations
14.
Chang, Jui-Fang, Liang‐Ying Wei, & Ching‐Hsue Cheng. (2009). ANFIS-based adaptive expectation model for forecasting stock index. International journal of innovative computing, information & control. 5(7). 1949–1958. 4 indexed citations
15.
Cheng, Ching‐Hsue & Liang‐Ying Wei. (2009). One step-ahead ANFIS time series model for forecasting electricity loads. Optimization and Engineering. 11(2). 303–317. 35 indexed citations
16.
Cheng, Ching‐Hsue, Liang‐Ying Wei, & You‐Shyang Chen. (2009). Fusion ANFIS models based on multi-stock volatility causality for TAIEX forecasting. Neurocomputing. 72(16-18). 3462–3468. 34 indexed citations
17.
Cheng, Ching‐Hsue & Liang‐Ying Wei. (2008). Volatility model based on multi-stock index for TAIEX forecasting. Expert Systems with Applications. 36(3). 6187–6191. 19 indexed citations
18.
Wei, Liang‐Ying & Ching‐Hsue Cheng. (2008). An entropy clustering analysis based on genetic algorithm. Journal of Intelligent & Fuzzy Systems. 19(4-5). 235–241. 7 indexed citations
19.
Cheng, Ching‐Hsue, et al.. (2007). Improving Relational Database Quality Based on Adaptive Learning Method for Estimating Null Value. 81–81. 4 indexed citations
20.
Wei, Liang‐Ying, Cheng-Lung Huang, & Chien-Hsiun Chen. (2005). Data mining of the GAW14 simulated data using rough set theory and tree-based methods. BMC Genetics. 6(S1). S133–S133. 4 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Rui Neves Breakdown of academic impact, for papers by Chih-Sheng Lin Breakdown of academic impact, for papers by Rajashree Dash Breakdown of academic impact, for papers by Yakup Kara Breakdown of academic impact, for papers by Arash Ghanbari Breakdown of academic impact, for papers by Erkam Güreşen Breakdown of academic impact, for papers by Priyank Thakkar Breakdown of academic impact, for papers by Zhensong Chen Breakdown of academic impact, for papers by Saman Haratizadeh Breakdown of academic impact, for papers by S. Shahab
Rankless by CCL
2026