Gwo-Ching Liao

1.2k total citations
37 papers, 967 citations indexed

About

Gwo-Ching Liao is a scholar working on Electrical and Electronic Engineering, Management Science and Operations Research and Artificial Intelligence. According to data from OpenAlex, Gwo-Ching Liao has authored 37 papers receiving a total of 967 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Electrical and Electronic Engineering, 10 papers in Management Science and Operations Research and 7 papers in Artificial Intelligence. Recurrent topics in Gwo-Ching Liao's work include Energy Load and Power Forecasting (27 papers), Electric Power System Optimization (17 papers) and Smart Grid Energy Management (13 papers). Gwo-Ching Liao is often cited by papers focused on Energy Load and Power Forecasting (27 papers), Electric Power System Optimization (17 papers) and Smart Grid Energy Management (13 papers). Gwo-Ching Liao collaborates with scholars based in Taiwan and China. Gwo-Ching Liao's co-authors include Ta‐Peng Tsao, Whei-Min Lin, Jong‐Chen Chen, Tianfeng Lu, Ziwen Liang, Tao Wu, An‐Chou Yeh, Rong‐Ching Wu and Robert Wu and has published in prestigious journals such as Expert Systems with Applications, Energy and IEEE Transactions on Evolutionary Computation.

In The Last Decade

Gwo-Ching Liao

35 papers receiving 889 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gwo-Ching Liao Taiwan 15 759 264 176 118 76 37 967
Mao Tan China 15 623 0.8× 172 0.7× 149 0.8× 103 0.9× 46 0.6× 56 853
Abdulaziz Almalaq Saudi Arabia 18 657 0.9× 258 1.0× 219 1.2× 64 0.5× 83 1.1× 37 939
Oveis Abedinia Iran 15 909 1.2× 272 1.0× 228 1.3× 116 1.0× 132 1.7× 29 1.2k
Ryuichi Yokoyama Japan 15 797 1.1× 507 1.9× 126 0.7× 58 0.5× 115 1.5× 146 1.1k
Yvon Bésanger France 15 773 1.0× 437 1.7× 80 0.5× 60 0.5× 34 0.4× 61 886
K. Chandrasekaran India 19 887 1.2× 310 1.2× 242 1.4× 33 0.3× 47 0.6× 48 1.2k
Oveis Abedinia Iran 13 615 0.8× 247 0.9× 112 0.6× 26 0.2× 73 1.0× 21 810
Gonggui Chen China 17 801 1.1× 310 1.2× 136 0.8× 28 0.2× 75 1.0× 49 991
Yingchao Dong China 14 318 0.4× 108 0.4× 163 0.9× 42 0.4× 66 0.9× 24 584
C. Christober Asir Rajan India 15 1.0k 1.4× 423 1.6× 120 0.7× 63 0.5× 30 0.4× 117 1.2k

Countries citing papers authored by Gwo-Ching Liao

Since Specialization
Citations

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

Fields of papers citing papers by Gwo-Ching Liao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gwo-Ching Liao. 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 Gwo-Ching Liao. The network helps show where Gwo-Ching Liao may publish in the future.

Co-authorship network of co-authors of Gwo-Ching Liao

This figure shows the co-authorship network connecting the top 25 collaborators of Gwo-Ching Liao. A scholar is included among the top collaborators of Gwo-Ching Liao 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 Gwo-Ching Liao. Gwo-Ching Liao 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.
Liao, Gwo-Ching, et al.. (2024). Applying deep reinforcement learning to solve the low-carbon economic dispatch problem in smart microgrids. Journal of Physics Conference Series. 2878(1). 12005–12005. 1 indexed citations
2.
Liao, Gwo-Ching, et al.. (2023). Application of a novel generative adversarial network to wind power forecasting. Journal of Physics Conference Series. 2631(1). 12022–12022.
3.
Liao, Gwo-Ching. (2013). The optimal economic dispatch of smart Microgrid including Distributed Generation. 473–477. 26 indexed citations
4.
Liao, Gwo-Ching. (2012). Solve environmental economic dispatch of Smart MicroGrid containing distributed generation system – Using chaotic quantum genetic algorithm. International Journal of Electrical Power & Energy Systems. 43(1). 779–787. 124 indexed citations
5.
Liao, Gwo-Ching, et al.. (2012). Torque Vibrations on the Mechanism of Wind Turbine Generators Excited by Balanced Network Faults. 25. 1–4. 1 indexed citations
6.
7.
Liao, Gwo-Ching. (2012). Integrated Isolation Niche and Immune Genetic Algorithm for solving Bid-Based Dynamic Economic Dispatch. International Journal of Electrical Power & Energy Systems. 42(1). 264–275. 19 indexed citations
8.
Liao, Gwo-Ching. (2011). Bid-based economic electrical load dispatch using improved genetic algorithm. Asian Control Conference. 1387–1392. 4 indexed citations
9.
Liao, Gwo-Ching. (2011). An improved fuzzy neural networks approach for short-term electrical load forecasting. Asian Control Conference. 596–601. 2 indexed citations
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12.
Chen, Jong‐Chen & Gwo-Ching Liao. (2007). Data differentiation and parameter analysis on the weight changes of premature babies with an artificial neuromolecular system. Expert Systems with Applications. 34(4). 2896–2904.
13.
Liao, Gwo-Ching. (2007). A Novel Particle Swarm Optimization Approach Combined with Fuzzy Neural Networks for Short-Term Load Forecasting. IEEE Power Engineering Society General Meeting. 1–6. 10 indexed citations
14.
Liao, Gwo-Ching & Ta‐Peng Tsao. (2006). Application of a fuzzy neural network combined with a chaos genetic algorithm and simulated annealing to short-term load forecasting. IEEE Transactions on Evolutionary Computation. 10(3). 330–340. 164 indexed citations
15.
Liao, Gwo-Ching. (2006). An evolutionary fuzzy neural network approach for short-term electric power load forecasting. 2006 IEEE Power Engineering Society General Meeting. pas 100. 6 pp.–6 pp.. 3 indexed citations
16.
Lu, Tianfeng, Jong‐Chen Chen, & Gwo-Ching Liao. (2006). Aggressive or conservative, general or specific? A study of organizations adopting different learning strategies in an artificial world. Expert Systems with Applications. 34(2). 1018–1027. 4 indexed citations
17.
Liao, Gwo-Ching. (2005). Short-term thermal generation scheduling using improved immune algorithm. Electric Power Systems Research. 76(5). 360–373. 21 indexed citations
18.
Liao, Gwo-Ching & Ta‐Peng Tsao. (2005). Using chaos search immune genetic and fuzzy system for short-term unit commitment algorithm. International Journal of Electrical Power & Energy Systems. 28(1). 1–12. 21 indexed citations
19.
Liao, Gwo-Ching. (2005). A new method for short term electric load forecasting. 2. 1165–1168. 2 indexed citations
20.
Liao, Gwo-Ching & Ta‐Peng Tsao. (2004). Integrating evolving fuzzy neural networks and tabu search for short term load forecasting. 31. 755–762. 3 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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