Ping‐Feng Pai

5.2k citations

104 papers · 4.2k · 1 hit paper · h-index 30

Impact in

Management Science and Operations Research top 0.2%
- Stock Market Forecasting Methods
- Forecasting Techniques and Applications
- Multi-Criteria Decision Making
Environmental Engineering top 5%
- Hydrological Forecasting Using AI

Papers in

Management Science and Operations Research 38
- Forecasting Techniques and Applications 16
- Stock Market Forecasting Methods 10
- Multi-Criteria Decision Making 10
Industrial and Manufacturing Engineering 8

Co-authors: Wei‐Chiang Hong (17 shared papers)Chih-Sheng Lin (4 shared papers)Kuo-Ping Lin (24 shared papers)Ping-Teng Chang (10 shared papers)Jung-Pin Lai (11 shared papers)Ming‐Lang Tseng (1 shared paper)Wenchang Wang (1 shared paper)Ming-Fu Hsu (8 shared papers)
Journals: Electronics (10 papers)Expert Systems with Applications (7 papers)The International Journal of Advanced Manufacturing Technology (7 papers)Neural Computing and Applications (4 papers)Water Resources Management (4 papers)
Partner nations: Taiwan United States Japan

In The Last Decade

Ping‐Feng Pai

98 papers receiving 4k citations

Ping‐Feng Pai's Hit Papers

align trajectories log scale

A hybrid ARIMA and support vector machines model in stock price forecasting 2004 · 788 citations

What are hit papers?

Paper score: A paper's citations measured against the top-1% bar of its own field and year: the square root of citations ÷ bar, so 1 means right at the bar and 2 means four times its citations. The bar blends the citation counts that enter the top 1% of the paper's subfields in its year (weighted 89.5%), of those subfields over all years (0.5%) and of its year across all fields (10%); a subfield and year with fewer than 400 papers takes its year's bar. Papers from 2026 are not scored yet: in an unfinished year, when a paper appeared matters more than how it is cited.

Hit paper: A paper cited at least 1.5× the top-1% bar of its field and year: a paper score of at least √1.5.

2004 Omega

Peers

Countries citing papers authored by Ping‐Feng Pai

Since Specialization

Citations

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

Fields of papers citing papers by Ping‐Feng Pai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ping‐Feng Pai. 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 Ping‐Feng Pai. The network helps show where Ping‐Feng Pai may publish in the future.

Co-authors

The 25 scholars most cited alongside Ping‐Feng Pai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ping‐Feng Pai Line = papers co-authored together Ping‐Feng Pai links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 104 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	A hybrid ARIMA and support vector machines model in stock price forecasting Omega ·Ping‐Feng Pai, Chih-Sheng Lin Hit paper breakdown →	2004	788
2	Support vector machines with simulated annealing algorithms in electricity load forecasting Energy Conversion and Management ·Ping‐Feng Pai, Wei‐Chiang Hong	2005	325
3	Forecasting regional electricity load based on recurrent support vector machines with genetic algorithms Electric Power Systems Research ·Ping‐Feng Pai, Wei‐Chiang Hong	2005	316
4	Sustainable supply chain management using approximate fuzzy DEMATEL method Resources Conservation and Recycling ·Kuo-Ping Lin, Ming‐Lang Tseng, Ping‐Feng Pai	2017	180
5	A Survey of Machine Learning Models in Renewable Energy Predictions Applied Sciences ·Jung-Pin Lai, Yu-Ming Chang, Chieh-Huang Chen, Ping‐Feng Pai	2020	171
6	Software reliability forecasting by support vector machines with simulated annealing algorithms Quality Engineering ·Ping‐Feng Pai, Wei‐Chiang Hong	2005	154
7	System reliability forecasting by support vector machines with genetic algorithms Mathematical and Computer Modelling ·Ping‐Feng Pai	2006	112
8	Solar power output forecasting using evolutionary seasonal decomposition least-square support vector regression Journal of Cleaner Production ·Kuo-Ping Lin, Ping‐Feng Pai	2015	111
9	Time series forecasting by a seasonal support vector regression model Expert Systems with Applications ·Ping‐Feng Pai, Kuo-Ping Lin, Chi-Shen Lin, Ping-Teng Chang	2009	107
10	Using Machine Learning Models and Actual Transaction Data for Predicting Real Estate Prices Applied Sciences ·Ping‐Feng Pai, Wenchang Wang	2020	98
11	An Improved Neural Network Model in Forecasting Arrivals Annals of Tourism Research ·Ping‐Feng Pai, Wei‐Chiang Hong	2005	93
12	Potential assessment of the support vector regression technique in rainfall forecasting Water Resources Management ·Wei‐Chiang Hong, Ping‐Feng Pai	2006	93
13	A support vector machine-based model for detecting top management fraud Knowledge-Based Systems ·Ping‐Feng Pai, Ming-Fu Hsu, Ming‐Chieh Wang	2010	93
14	Tourism demand forecasting using novel hybrid system Expert Systems with Applications ·Ping‐Feng Pai, Kuo-Chen Hung, Kuo-Ping Lin	2013	84
15	Predicting Vehicle Sales by Sentiment Analysis of Twitter Data and Stock Market Values IEEE Access ·Ping‐Feng Pai, Chia‐Hsin Liu	2018	83
16	Predicting engine reliability by support vector machines The International Journal of Advanced Manufacturing Technology ·Wei‐Chiang Hong, Ping‐Feng Pai	2005	81
17	Forecasting concentrations of air pollutants by logarithm support vector regression with immune algorithms Applied Mathematics and Computation ·Kuo-Ping Lin, Ping‐Feng Pai, Shun-Ling Yang	2010	77
18	Revenue forecasting using a least-squares support vector regression model in a fuzzy environment Information Sciences ·Kuo-Ping Lin, Ping‐Feng Pai, Yuming Lu, Ping-Teng Chang	2011	75
19	A recurrent support vector regression model in rainfall forecasting Hydrological Processes ·Ping‐Feng Pai, Wei‐Chiang Hong	2006	64
20	Deep Belief Networks With Genetic Algorithms in Forecasting Wind Speed IEEE Access ·Kuo-Ping Lin, Ping‐Feng Pai, Yi-Ju Ting	2019	54

About Ping‐Feng Pai

Ping‐Feng Pai is a scholar working on Management Science and Operations Research, Industrial and Manufacturing Engineering, Health Information Management, Accounting and Artificial Intelligence, having authored 104 papers that have together received 4.2k indexed citations. Recurring topics across this work include Forecasting Techniques and Applications (16 papers), Stock Market Forecasting Methods (10 papers), Multi-Criteria Decision Making (10 papers), Rough Sets and Fuzzy Logic (7 papers), Data Mining and Machine Learning Applications (7 papers), Artificial Intelligence in Healthcare (6 papers), Financial Distress and Bankruptcy Prediction (6 papers) and Energy Load and Power Forecasting (6 papers). The work is most often cited by research in Management Science and Operations Research (1.4k citations), Environmental Engineering (227 citations), Artificial Intelligence (611 citations), Software (78 citations) and Industrial and Manufacturing Engineering (135 citations). Ping‐Feng Pai has collaborated with scholars based in Taiwan, United States and Japan. Frequent co-authors include Wei‐Chiang Hong, Chih-Sheng Lin, Kuo-Ping Lin, Ping-Teng Chang, Jung-Pin Lai, Ming‐Lang Tseng, Wenchang Wang, Ming-Fu Hsu, Yu-Ming Chang and Kuo-Chen Hung. Their work appears in journals such as Electronics, Expert Systems with Applications, The International Journal of Advanced Manufacturing Technology, Neural Computing and Applications and Water Resources Management.

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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Ping‐Feng Pai's Hit Papers

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Fields of papers citing papers by Ping‐Feng Pai

All Works

About Ping‐Feng Pai

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