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2020 – today
- 2023
[j32]Yu-Shan Li, Ping-Feng Pai
, Ying-Lei Lin:
Forecasting inflation rates be extreme gradient boosting with the genetic algorithm. J. Ambient Intell. Humaniz. Comput. 14(3): 2211-2220 (2023)- 2020
- [j31]Yi-Ting Huang, Ping-Feng Pai:
Using the Least Squares Support Vector Regression to Forecast Movie Sales with Data from Twitter and Movie Databases. Symmetry 12(4): 625 (2020)
2010 – 2019
- 2019
- [j30]Kuo-Ping Lin, Ping-Feng Pai, Yi-Ju Ting:
Deep Belief Networks With Genetic Algorithms in Forecasting Wind Speed. IEEE Access 7: 99244-99253 (2019) - 2018
- [j29]Ping-Feng Pai, Chia-Hsin Liu:
Predicting Vehicle Sales by Sentiment Analysis of Twitter Data and Stock Market Values. IEEE Access 6: 57655-57662 (2018) - [j28]Ping-Feng Pai, Ling-Chuang Hong, Kuo-Ping Lin:
Using Internet Search Trends and Historical Trading Data for Predicting Stock Markets by the Least Squares Support Vector Regression Model. Comput. Intell. Neurosci. 2018: 6305246:1-6305246:15 (2018) - 2017
- [j27]Ping-Feng Pai, Lan-Hung ChangLiao, Kuo-Ping Lin:
Analyzing basketball games by a support vector machines with decision tree model. Neural Comput. Appl. 28(12): 4159-4167 (2017) - 2016
- [j26]Ping-Feng Pai, Lei-Chun Chen, Kuo-Ping Lin:
A hybrid data mining model in analyzing corporate social responsibility. Neural Comput. Appl. 27(3): 749-760 (2016) - 2015
- [j25]Ping-Feng Pai, Yi-Shien Tan, Ming-Fu Hsu:
Credit Rating Analysis by the Decision-Tree Support Vector Machine with Ensemble Strategies. Int. J. Fuzzy Syst. 17(4): 521-530 (2015) - 2014
- [j24]Ping-Feng Pai, Kuo-Chen Hung, Kuo-Ping Lin:
Tourism demand forecasting using novel hybrid system. Expert Syst. Appl. 41(8): 3691-3702 (2014) - [j23]Ping-Feng Pai, Chen-Tung Chen, Wei-Zhan Hung:
Applying linguistic information and intersection concept to improve effectiveness of multi-criteria decision analysis technology. Int. J. Inf. Technol. Decis. Mak. 13(2): 291-316 (2014) - [j22]Ping-Feng Pai, Ming-Fu Hsu, Lin Lin:
Enhancing decisions with life cycle analysis for risk management. Neural Comput. Appl. 24(7-8): 1717-1724 (2014) - [j21]Ping-Feng Pai, Chen-Tung Chen, Yu-Mei Hung, Wei-Zhan Hung, Ying-Chieh Chang:
A group decision classifier with particle swarm optimization and decision tree for analyzing achievements in mathematics and science. Neural Comput. Appl. 25(7-8): 2011-2023 (2014) - [c16]Chen-Tung Chen, Ping-Feng Pai, Wei-Zhan Hung:
Deal with Linguistic Multi-Criteria Decision Making Problem Based on Sequential Multi-person Game Methodology. IEA/AIE (1) 2014: 500-510 - 2013
- [j20]Ping-Teng Chang, Lung-Ting Hung, Ping-Feng Pai, Kuo-Ping Lin:
Improving project-profit prediction using a two-stage forecasting system. Comput. Ind. Eng. 66(4): 800-807 (2013) - [j19]Kuo-Ping Lin, Ping-Feng Pai, Yu-Ming Lu, Ping-Teng Chang:
Revenue forecasting using a least-squares support vector regression model in a fuzzy environment. Inf. Sci. 220: 196-209 (2013) - [c15]Chen-Tung Chen, Ping-Feng Pai, Wei-Zhan Hung:
Extending the strategy game from multi-criteria considerations with linguistic variables. FSKD 2013: 273-278 - 2012
- [j18]Kuo-Ping Lin, Hung-Pin Ho, Kuo-Chen Hung, Ping-Feng Pai:
Combining fuzzy weight average with fuzzy inference system for material substitution selection in electric industry. Comput. Ind. Eng. 62(4): 1034-1045 (2012) - 2011
- [j17]Kuo-Ping Lin, Ping-Feng Pai, Shun-Lin Yang:
Forecasting concentrations of air pollutants by logarithm support vector regression with immune algorithms. Appl. Math. Comput. 217(12): 5318-5327 (2011) - [j16]Ping-Feng Pai, Ya-Hsin Chang, Ming-Fu Hsu, Jachih Fu, Hsin-Hua Chen:
A hybrid kernel principal component analysis and support vector machine model for analysing sonographic features of parotid glands in Sjogren's syndrome. Int. J. Math. Model. Numer. Optimisation 2(1): 98-108 (2011) - [j15]Ping-Feng Pai, Ming-Fu Hsu, Ming-Chieh Wang:
A support vector machine-based model for detecting top management fraud. Knowl. Based Syst. 24(2): 314-321 (2011) - [c14]Chen-Tung Chen, Ping-Feng Pai, Wei-Zhan Hung:
Applying multi-criteria decision classifier in multi-class classification. FSKD 2011: 607-610 - [c13]Chen-Tung Chen, Ping-Feng Pai, Wei-Zhan Hung:
Handling fuzzy decision making problem based on linguistic information and intersection concept. FUZZ-IEEE 2011: 1504-1509 - [p1]Ping-Feng Pai, Ming-Fu Hsu:
An Enhanced Support Vector Machines Model for Classification and Rule Generation. Computational Optimization, Methods and Algorithms 2011: 241-258 - 2010
- [j14]Ping-Feng Pai, Yi-Jia Lyu, Yu-Min Wang:
Analyzing academic achievement of junior high school students by an improved rough set model. Comput. Educ. 54(4): 889-900 (2010) - [j13]Kuo-Ping Lin, Ping-Teng Chang, Kuo-Chen Hung, Ping-Feng Pai:
A simulation of vendor managed inventory dynamics using fuzzy arithmetic operations with genetic algorithms. Expert Syst. Appl. 37(3): 2571-2579 (2010) - [j12]Ping-Feng Pai, Kuo-Ping Lin, Chi-Shen Lin, Ping-Teng Chang:
Time series forecasting by a seasonal support vector regression model. Expert Syst. Appl. 37(6): 4261-4265 (2010) - [j11]Kuo-Ping Lin, Ping-Feng Pai:
A fuzzy support vector regression model for business cycle predictions. Expert Syst. Appl. 37(7): 5430-5435 (2010) - [j10]Ping-Feng Pai, Shi-Yu Chen, Chao-Wei Huang, Ya-Hsin Chang:
Analyzing foreign exchange rates by rough set theory and directed acyclic graph support vector machines. Expert Syst. Appl. 37(8): 5993-5998 (2010) - [j9]Chen-Tung Chen, Ping-Feng Pai, Wei-Zhan Hung:
An Integrated Methodology using Linguistic PROMETHEE and Maximum Deviation Method for Third-party Logistics Supplier Selection. Int. J. Comput. Intell. Syst. 3(4): 438-451 (2010) - [j8]Hsin-Hua Chen, Ping-Feng Pai, Ying-Zhieh Cho, Fong-Chuan Lee, Jachih Fu:
An improved support vector machines model in medical data analysis. Int. J. Math. Model. Numer. Optimisation 1(3): 168-184 (2010) - [c12]Ping-Feng Pai, Ming-Fu Hsu, Ming-Chieh Wang:
Computer-assisted audit techniques based on an enhanced rough set model. NCM 2010: 207-212
2000 – 2009
- 2009
- [j7]Ping-Feng Pai, Tai-Chi Chen:
Rough set theory with discriminant analysis in analyzing electricity loads. Expert Syst. Appl. 36(5): 8799-8806 (2009) - [j6]Ping-Feng Pai, Shun-Lin Yang, Ping-Teng Chang:
Forecasting output of integrated circuit industry by support vector regression models with marriage honey-bees optimization algorithms. Expert Syst. Appl. 36(7): 10746-10751 (2009) - [c11]Ping-Feng Pai, Ying-Chieh Chang, Yu-Pin Hu:
Management of Wireless Local Area Networks by Artificial Neural Networks with Principal Components Analysis. ACIIDS 2009: 341-345 - 2007
- [c10]Wei-Chiang Hong, Young-Jou Lai, Ping-Feng Pai, Shao-Lun Lee, Shun-Lin Yang:
Composite of support vector regression and evolutionary algorithms in car-rental revenue forecasting. IEEE Congress on Evolutionary Computation 2007: 2872-2878 - [c9]Ping-Feng Pai, Kuo-Ping Lin, Ping-Teng Chang:
Potential Assessment of an Ellipsoidal Neural Fuzzy Time Series Model for Freeway Traffic Prediction. ICANNGA (1) 2007: 631-639 - [c8]Ping-Feng Pai, Yuying Huang:
Using Support Vector Machines and Rough Sets Theory for Classifying Faulty Types of Diesel Engine. ICCSA (1) 2007: 550-561 - [c7]Wei-Chiang Hong, Ping-Feng Pai, Shun-Lin Yang, Chien-Yuan Lai:
Continuous Ant Colony Optimization in a SVR Urban Traffic Forecasting Model. IWANN 2007: 765-773 - 2006
- [j5]Ping-Teng Chang, Ping-Feng Pai, Kuo-Ping Lin, Ming-Shiu Wu:
Applying fuzzy arithmetic to the system dynamics for the customer-producer-employment model. Int. J. Syst. Sci. 37(10): 673-698 (2006) - [j4]Ping-Feng Pai, Wei-Chiang Hong:
Software reliability forecasting by support vector machines with simulated annealing algorithms. J. Syst. Softw. 79(6): 747-755 (2006) - [j3]Ping-Feng Pai:
System reliability forecasting by support vector machines with genetic algorithms. Math. Comput. Model. 43(3-4): 262-274 (2006) - [j2]Ping-Feng Pai, Kuo-Ping Lin:
Application of Hybrid Learning Neural Fuzzy Systems in Reliability Prediction. Qual. Reliab. Eng. Int. 22(2): 199-211 (2006) - [c6]Wei-Chiang Hong, Ping-Feng Pai, Shun-Lin Yang, Robert Theng:
Highway traffic forecasting by support vector regression model with tabu search algorithms. IJCNN 2006: 1617-1621 - [c5]Ping-Feng Pai, Yuying Huang:
Using Directed Acyclic Graph Support Vector Machines with Tabu Search for Classifying Faulty Product Types. ISNN (2) 2006: 1117-1125 - [c4]Ping-Feng Pai, Wei-Chiang Hong, Feng-Min Lai, Jia-Hroung Wu, Shun-Lin Yang:
Feasibility Assessment of Support Vector Regression Models with Immune Algorithms in Predicting Fatigue Life of Composites. JCIS 2006 - 2005
- [j1]Ping-Feng Pai, Wei-Chiang Hong, Chih-Shen Lin:
Forecasting Electric Load by Support Vector Machines with Genetic Algorithms. J. Adv. Comput. Intell. Intell. Informatics 9(2): 134-141 (2005) - [c3]Ping-Feng Pai, Wei-Chiang Hong, Chih-Sheng Lin:
Forecasting Tourism Demand Using a Multifactor Support Vector Machine Model. CIS (1) 2005: 512-519 - [c2]Wei-Chiang Hong, Ping-Feng Pai, Chen-Tung Chen, Ping-Teng Chang:
Recurrent Support Vector Machines in Reliability Prediction. ICNC (1) 2005: 619-629 - [c1]Wei-Chiang Hong, Ping-Feng Pai, Yuying Huang, Shun-Lin Yang:
Application of Support Vector Machines in Predicting Employee Turnover Based on Job Performance. ICNC (1) 2005: 668-674
Coauthor Index
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