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Shang-Ming Zhou
Person information
- affiliation: Swansea University, UK
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2020 – today
- 2023
- [c20]Omobolanle Omisade
, Alexander E. Gegov, Shang-Ming Zhou
, Alice Good, Catherine Tryfona, Sandeep Singh Sengar
, Amie-Louise Prior, Bangli Liu, Taiwo Adedeji
, Carrie M. Toptan:
Explainable Artificial Intelligence and Mobile Health for Treating Eating Disorders in Young Adults with Autism Spectrum Disorder Based on the Theory of Change: A Mixed Method Protocol. FICTA (2) 2023: 31-44 - 2022
- [j28]Lin Huo, Lin Bai, Shang-Ming Zhou
:
Automatically Generating Natural Language Descriptions of Images by a Deep Hierarchical Framework. IEEE Trans. Cybern. 52(8): 7441-7452 (2022) - 2021
- [j27]Shang-Ming Zhou
, Francisco Chiclana
, Robert I. John
, Jonathan M. Garibaldi
, Lin Huo
:
Type-1 OWA Operators in Aggregating Multiple Sources of Uncertain Information: Properties and Real-World Applications in Integrated Diagnosis. IEEE Trans. Fuzzy Syst. 29(8): 2112-2121 (2021) - [c19]Jamie Andrew Duell, Xiuyi Fan, Bruce Burnett, Gert Aarts, Shang-Ming Zhou
:
A Comparison of Explanations Given by Explainable Artificial Intelligence Methods on Analysing Electronic Health Records. BHI 2021: 1-4 - [c18]Marcin Kapcia, Hassan Eshkiki
, Jamie Andrew Duell, Xiuyi Fan, Shang-Ming Zhou
, Benjamin Mora
:
ExMed: An AI Tool for Experimenting Explainable AI Techniques on Medical Data Analytics. ICTAI 2021: 841-845 - [i2]Jamie Andrew Duell, Monika Seisenberger, Gert Aarts, Shang-Ming Zhou, Xiuyi Fan:
Towards a Shapley Value Graph Framework for Medical peer-influence. CoRR abs/2112.14624 (2021)
2010 – 2019
- 2019
- [j26]Haider Raza
, Dheeraj Rathee, Shang-Ming Zhou
, Hubert Cecotti, Girijesh Prasad:
Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface. Neurocomputing 343: 154-166 (2019) - 2018
- [i1]Haider Raza, Dheeraj Rathee, Shang-Ming Zhou, Hubert Cecotti, Girijesh Prasad:
Covariate Shift Estimation based Adaptive Ensemble Learning for Handling Non-Stationarity in Motor Imagery related EEG-based Brain-Computer Interface. CoRR abs/1805.01044 (2018) - 2017
- [j25]David A. Elizondo, Shang-Ming Zhou
, Charalambos Chrysostomou
:
Light source detection for digital images in noisy scenes: a neural network approach. Neural Comput. Appl. 28(5): 899-909 (2017) - 2015
- [j24]Pan Wang, Ricardo Valerdi, Shang-Ming Zhou
, Ling Li:
Introduction: Advances in IoT research and applications. Inf. Syst. Frontiers 17(2): 239-241 (2015) - 2014
- [j23]Francisco Mata, Luis G. Pérez, Shang-Ming Zhou, Francisco Chiclana:
Type-1 OWA methodology to consensus reaching processes in multi-granular linguistic contexts. Knowl. Based Syst. 58: 11-22 (2014) - [j22]Zu De Zhou, Ricardo Valerdi, Shang-Ming Zhou
, Li Wang:
Guest Editorial Special Section on IoT. IEEE Trans. Ind. Informatics 10(2): 1413-1416 (2014) - [c17]Jingjing Deng
, Xianghua Xie
, Shang-Ming Zhou
:
Conversational Interaction Recognition Based on Bodily and Facial Movement. ICIAR (1) 2014: 237-245 - [c16]Shang-Ming Zhou
, Muhammad A. Rahman, Mark D. Atkinson, Sinead Brophy
:
Mining textual data from primary healthcare records: Automatic identification of patient phenotype cohorts. IJCNN 2014: 3621-3627 - [c15]Wanli Ma
, Dat Tran
, Trung Le, Hong Lin, Shang-Ming Zhou
:
Using EEG artifacts for BCI applications. IJCNN 2014: 3628-3635 - 2013
- [j21]Francisco Chiclana
, Shang-Ming Zhou
:
Type-Reduction of General Type-2 Fuzzy Sets: The Type-1 OWA Approach. Int. J. Intell. Syst. 28(5): 505-522 (2013) - 2012
- [j20]Jonathan M. Garibaldi
, Shang-Ming Zhou
, Xiao-Ying Wang, Robert Ivor John
, Ian O. Ellis
:
Incorporation of expert variability into breast cancer treatment recommendation in designing clinical protocol guided fuzzy rule system models. J. Biomed. Informatics 45(3): 447-459 (2012) - [j19]Zu De Zhou, Ricardo Valerdi, Shang-Ming Zhou
:
Guest Editorial Special Section on Enterprise Systems. IEEE Trans. Ind. Informatics 8(3): 630 (2012) - [j18]Ling Li, Ri-Li Ge, Shang-Ming Zhou
, Ricardo Valerdi:
Guest EditorialIntegrated Healthcare Information Systems. IEEE Trans. Inf. Technol. Biomed. 16(4): 515-517 (2012) - 2011
- [j17]Shang-Ming Zhou
, Francisco Chiclana
, Robert Ivor John
, Jonathan M. Garibaldi
:
Alpha-Level Aggregation: A Practical Approach to Type-1 OWA Operation for Aggregating Uncertain Information with Applications to Breast Cancer Treatments. IEEE Trans. Knowl. Data Eng. 23(10): 1455-1468 (2011) - [c14]Francisco Chiclana
, Shang-Ming Zhou
:
The Type-1 OWA Operator and the Centroid of Type-2 Fuzzy Sets. EUSFLAT Conf. 2011: 15-20 - [p2]Shang-Ming Zhou
, Francisco Chiclana
, Robert Ivor John, Jonathan M. Garibaldi
:
Fuzzification of the OWA Operators for Aggregating Uncertain Information with Uncertain Weights. Recent Developments in the Ordered Weighted Averaging Operators 2011: 91-109 - 2010
- [j16]Pan Wang, Lida Xu, Shang-Ming Zhou
, Zhun Fan
, Youfeng Li, Shan Feng:
A novel Bayesian learning method for information aggregation in modular neural networks. Expert Syst. Appl. 37(2): 1071-1074 (2010) - [j15]Shang-Ming Zhou
, Robert Ivor John
, Francisco Chiclana
, Jonathan M. Garibaldi
:
On aggregating uncertain information by type-2 OWA operators for soft decision making. Int. J. Intell. Syst. 25(6): 540-558 (2010) - [c13]Shang-Ming Zhou
, Ronan A. Lyons, Mike B. Gravenor:
Construction of parsimonious Takagi-Sugeno fuzzy rule based model in characterising impacts of child health, socioeconomic deprivations on educational outcomes. FUZZ-IEEE 2010: 1-8 - [c12]Shang-Ming Zhou
, Ronan A. Lyons, Owen Bodger
, Joanne C. Demmler
, Mark D. Atkinson:
SVM with entropy regularization and particle swarm optimization for identifying children's health and socioeconomic determinants of education attainments using linked datasets. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [j14]Shang-Ming Zhou
, John Q. Gan
, Lida Xu, Robert Ivor John
:
Fuzziness index driven fuzzy relaxation algorithm and applications to image processing. Ann. Oper. Res. 168(1): 119-131 (2009) - [j13]Shang-Ming Zhou
, Jonathan M. Garibaldi
, Robert Ivor John
, Francisco Chiclana
:
On Constructing Parsimonious Type-2 Fuzzy Logic Systems via Influential Rule Selection. IEEE Trans. Fuzzy Syst. 17(3): 654-667 (2009) - [j12]Shang-Ming Zhou
, John Q. Gan
:
Extracting Takagi-Sugeno Fuzzy Rules with Interpretable Submodels via Regularization of Linguistic Modifiers. IEEE Trans. Knowl. Data Eng. 21(8): 1191-1204 (2009) - [c11]Shang-Ming Zhou
, Jonathan M. Garibaldi
, Francisco Chiclana
, Robert Ivor John
, Xiao-Ying Wang:
Type-1 OWA operator based non-stationary fuzzy decision support systems for breast cancer treatments. FUZZ-IEEE 2009: 175-180 - [c10]Xiao-Ying Wang, Jonathan M. Garibaldi
, Shang-Ming Zhou
, Robert Ivor John
:
Methods of interpretation of a non-stationary fuzzy system for the treatment of breast cancer. FUZZ-IEEE 2009: 1187-1192 - 2008
- [j11]Shang-Ming Zhou
, John Q. Gan
:
Low-level interpretability and high-level interpretability: a unified view of data-driven interpretable fuzzy system modelling. Fuzzy Sets Syst. 159(23): 3091-3131 (2008) - [j10]Shang-Ming Zhou
, Francisco Chiclana
, Robert Ivor John
, Jonathan M. Garibaldi
:
Type-1 OWA operators for aggregating uncertain information with uncertain weights induced by type-2 linguistic quantifiers. Fuzzy Sets Syst. 159(24): 3281-3296 (2008) - [j9]Shang-Ming Zhou
, John Q. Gan
, Francisco Sepulveda:
Classifying mental tasks based on features of higher-order statistics from EEG signals in brain-computer interface. Inf. Sci. 178(6): 1629-1640 (2008) - [c9]Shang-Ming Zhou
, Robert Ivor John, Xiao-Ying Wang, Jonathan M. Garibaldi
, Ian O. Ellis
:
Compact fuzzy rules induction and feature extraction using SVM with particle swarms for breast cancer treatments. IEEE Congress on Evolutionary Computation 2008: 1469-1475 - [c8]Shang-Ming Zhou
, Francisco Chiclana
, Robert Ivor John, Jonathan M. Garibaldi
:
Type-2 OWA operators - aggregating type-2 fuzzy sets in soft decision making. FUZZ-IEEE 2008: 625-630 - [c7]Shang-Ming Zhou
, Francisco Chiclana
:
Inducing linguistic weights for type-1 OWA operators in soft decision making. FUZZ-IEEE 2008: 1626-1633 - [c6]David A. Elizondo, Shang-Ming Zhou
, Charalambos Chrysostomou
:
Surface Reconstruction Techniques Using Neural Networks to Recover Noisy 3D Scenes. ICANN (1) 2008: 857-866 - 2007
- [j8]Shang-Ming Zhou
, John Q. Gan
, Lida Xu, Robert I. John:
Interactive image enhancement by fuzzy relaxation. Int. J. Autom. Comput. 4(3): 229-235 (2007) - [j7]Shang-Ming Zhou
, John Q. Gan
:
Constructing L2-SVM-Based Fuzzy Classifiers in High-Dimensional Space With Automatic Model Selection and Fuzzy Rule Ranking. IEEE Trans. Fuzzy Syst. 15(3): 398-409 (2007) - [c5]William Blewitt, Shang-Ming Zhou
, Simon Coupland:
A Novel Approach to Type-2 Fuzzy Addition. FUZZ-IEEE 2007: 1-6 - [c4]Shang-Ming Zhou
, Robert I. John, Francisco Chiclana
, Jonathan M. Garibaldi
:
New Type-2 Rule Ranking Indices for Designing Parsimonious Interval Type-2 Fuzzy Logic Systems. FUZZ-IEEE 2007: 1-6 - 2006
- [b1]Shang-Ming Zhou:
Machine learning and intelligent data analysis for interpretable neuro-fuzzy system modelling. University of Essex, Colchester, UK, 2006 - [j6]Shang-Ming Zhou
, John Q. Gan
:
Constructing accurate and parsimonious fuzzy models with distinguishable fuzzy sets based on an entropy measure. Fuzzy Sets Syst. 157(8): 1057-1074 (2006) - [j5]Shang-Ming Zhou
, John Q. Gan:
A new fuzzy relaxation algorithm for image enhancement. Int. J. Knowl. Based Intell. Eng. Syst. 10(3): 181-192 (2006) - [c3]John Q. Gan, Shang-Ming Zhou
:
A New Fuzzy Membership Function with Applications in Interpretability Improvement of Neurofuzzy Models. ICIC (2) 2006: 183-194 - [p1]Shang-Ming Zhou
, John Q. Gan:
Multiple Objective Learning for Constructing Interpretable Takagi-Sugeno Fuzzy Model. Multi-Objective Machine Learning 2006: 385-403 - 2004
- [j4]Shang-Ming Zhou
, John Q. Gan:
An Unsupervised Kernel Based Fuzzy C-Means Clustering Algorithm With Kernel Normalisation. Int. J. Comput. Intell. Appl. 4(4): 355-374 (2004) - [c2]Shang-Ming Zhou
, John Q. Gan
:
Interpretability improvement of input space partitioning by merging fuzzy sets based on an entropy measure. FUZZ-IEEE 2004: 287-292 - [c1]Shang-Ming Zhou
, John Q. Gan:
Mercer Kernel, Fuzzy C-Means Algorithm, and Prototypes of Clusters. IDEAL 2004: 613-618 - 2003
- [j3]Shang-Ming Zhou
, Hong-Xing Li, Lida Xu:
A variational approach to intensity approximation for remote sensing images using dynamic neural networks. Expert Syst. J. Knowl. Eng. 20(4): 163-170 (2003) - 2001
- [j2]Shang-Ming Zhou
, Li Da Xu:
A new type of recurrent fuzzy neural network for modeling dynamic systems. Knowl. Based Syst. 14(5-6): 243-251 (2001)
1990 – 1999
- 1999
- [j1]Shang-Ming Zhou
, Li Da Xu:
Dynamic recurrent neural networks for a hybrid intelligent decision support system for the metallurgical industry. Expert Syst. J. Knowl. Eng. 16(4): 240-247 (1999)
Coauthor Index
aka: Robert I. John
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