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2020 – today
- 2023
[j19]Chien-Feng Kung, Pei-Yi Hao:
Fuzzy Least Squares Support Vector Machine with Fuzzy Hyperplane. Neural Process. Lett. 55(6): 7415-7446 (2023)- [j18]Jung-Hsien Chiang
, Chung-Yao Ma, Chi-Shiang Wang, Pei-Yi Hao:
An Adaptive, Context-Aware, and Stacked Attention Network-Based Recommendation System to Capture Users' Temporal Preference. IEEE Trans. Knowl. Data Eng. 35(4): 3404-3418 (2023) - [c20]Pei-Yi Hao:
Fuzzy Hyperplane Based K-SVCR Multi-class Classification with Its Applications to Stock Prediction Problem. ICAISC (1) 2023: 101-111 - [c19]Pei-Yi Hao:
Fuzzy Hyperplane Based Twin-KSVC and Its Applications to Stock Price Movement Direction Prediction Based on News Articles. PAAMS 2023: 125-136 - 2022
- [j17]Pei-Yi Hao, Jung-Hsien Chiang, Yu-De Chen:
Possibilistic classification by support vector networks. Neural Networks 149: 40-56 (2022) - [c18]Pei-Yi Hao:
Predicting the Trends of Stock Price By CNN-BiLSTM-AM and Fuzzy Twin Support Vector Machine From Social Networks. CSCI 2022: 819-825 - 2021
- [j16]Pei-Yi Hao, Chien-Feng Kung, Chun-Yang Chang, Jen-Bing Ou:
Predicting stock price trends based on financial news articles and using a novel twin support vector machine with fuzzy hyperplane. Appl. Soft Comput. 98: 106806 (2021) - [j15]Pei-Yi Hao:
Asymmetric Possibility and Necessity Regression by Twin-Support Vector Networks. IEEE Trans. Fuzzy Syst. 29(10): 3028-3042 (2021) - [c17]Pei-Yi Hao:
Predicting the Trends of Stock Price By Social Networks and Fuzzy Deep Support Vector Machine. SSCI 2021: 1-8 - 2020
- [j14]Pei-Yi Hao:
Dual possibilistic regression analysis using support vector networks. Fuzzy Sets Syst. 387: 1-34 (2020) - [c16]Pei-Yi Hao, Jen-Bing Ou, Kai-Xiang Zhuang:
Forecasting the Trends of Stock Price through Social Networks by Fuzzy Support Vector Machine with Possibility Measures. MISNC/IEMT 2020: 8:1-8:7 - [c15]Pei-Yi Hao:
Asymmetric Dual Possibilistic Regression Model by using Pairing nu Support Vector Networks. SSCI 2020: 588-594
2010 – 2019
- 2019
- [j13]Pei-Yi Hao, Weng-Hang Cheang, Jung-Hsien Chiang:
Real-time event embedding for POI recommendation. Neurocomputing 349: 1-11 (2019) - 2017
- [j12]Pei-Yi Hao:
Pairing support vector algorithm for data regression. Neurocomputing 225: 174-187 (2017) - [j11]Pei-Yi Hao:
Pair-v-SVR: A Novel and Efficient Pairing nu-Support Vector Regression Algorithm. IEEE Trans. Neural Networks Learn. Syst. 28(11): 2503-2515 (2017) - [c14]Pei-Yi Hao, Jen-Bing Ou:
Fuzzy Support Vector Classification Machine Using Possibility Inequality Measures. TAAI 2017: 17-20 - 2016
- [j10]Pei-Yi Hao:
Support vector classification with fuzzy hyperplane. J. Intell. Fuzzy Syst. 30(3): 1431-1443 (2016) - 2015
- [c13]Pei-Yi Hao:
A New Pairing Support Vector Regression. ACIIDS (1) 2015: 327-336 - 2014
- [c12]Pei-Yi Hao:
A New Fuzzy Support Vector Data Description Machine. IEA/AIE (1) 2014: 118-127 - 2013
- [c11]Pei-Yi Hao:
A new fuzzy maximal-margin spherical-structured multi-class support vector machine. ICMLC 2013: 241-246 - 2012
- [c10]Pei-Yi Hao, Chao-Yi Wu:
GPS GDOP approximation using support vector regression algorithm with parametric insensitive model. ICMLC 2012: 315-320 - 2011
- [c9]Pei-Yi Hao:
Possibilistic regression analysis by support vector machine. FUZZ-IEEE 2011: 889-894 - [c8]Pei-Yi Hao, Yu-De Chen:
A novel associative classification algorithm: A combination of LAC and CMAR with new measure of weighted effect of each rule group. ICMLC 2011: 891-896 - 2010
- [j9]Pei-Yi Hao:
New support vector algorithms with parametric insensitive/margin model. Neural Networks 23(1): 60-73 (2010) - [c7]Wei-Ming Chen, I-Lin Wu, Jung-Hsien Chiang, Pei-Yi Hao:
Prediction of subcelluar localization using maximal-margin spherical support vector machine. ICMLC 2010: 1476-1481
2000 – 2009
- 2009
- [j8]Pei-Yi Hao, Jung-Hsien Chiang, Yen-Hsiu Lin:
A new maximal-margin spherical-structured multi-class support vector machine. Appl. Intell. 30(2): 98-111 (2009) - [j7]Pei-Yi Hao:
Interval regression analysis using support vector networks. Fuzzy Sets Syst. 160(17): 2466-2485 (2009) - 2008
- [j6]Pei-Yi Hao:
Fuzzy one-class support vector machines. Fuzzy Sets Syst. 159(18): 2317-2336 (2008) - [j5]Pei-Yi Hao, Jung-Hsien Chiang:
Fuzzy Regression Analysis by Support Vector Learning Approach. IEEE Trans. Fuzzy Syst. 16(2): 428-441 (2008) - [c6]Pei-Yi Hao:
A fuzzy model of support vector classification algorithm. FUZZ-IEEE 2008: 299-304 - [c5]Pei-Yi Hao, Lung-Biao Tsai, Min-Shiu Lin:
A new Support Vector classification algorithm with parametric-margin model. IJCNN 2008: 420-425 - [c4]Pei-Yi Hao, Min-Shiu Lin, Lung-Biao Tsai:
A New Support Vector Machine with Fuzzy Hyper-Plane and Its Application to Evaluate Credit Risk. ISDA (3) 2008: 83-88 - 2007
- [j4]Pei-Yi Hao, Jung-Hsien Chiang, Yi-Kun Tu:
Hierarchically SVM classification based on support vector clustering method and its application to document categorization. Expert Syst. Appl. 33(3): 627-635 (2007) - [c3]Pei-Yi Hao, Yen-Hsiu Lin:
A New Multi-class Support Vector Machine with Multi-sphere in the Feature Space. IEA/AIE 2007: 756-765 - 2006
- [j3]Pei-Yi Hao, Jung-Hsien Chiang:
Pruning and Model-selecting Algorithms in the Rbf Frameworks Constructed by Support Vector Learning. Int. J. Neural Syst. 16(4): 283-294 (2006) - [c2]Pei-Yi Hao:
Pruning Support Vectors in the SVM Framework and Its Application to Face Detection. JCIS 2006 - 2004
- [j2]Jung-Hsien Chiang, Pei-Yi Hao:
Support vector learning mechanism for fuzzy rule-based modeling: a new approach. IEEE Trans. Fuzzy Syst. 12(1): 1-12 (2004) - 2003
- [j1]Jung-Hsien Chiang, Pei-Yi Hao:
A new kernel-based fuzzy clustering approach: support vector clustering with cell growing. IEEE Trans. Fuzzy Syst. 11(4): 518-527 (2003) - [c1]Pei-Yi Hao, Jung-Hsien Chiang:
A fuzzy model of support vector machine regression. FUZZ-IEEE 2003: 738-742
Coauthor Index
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