Wei Pang

Research output

Research output per year 2002 2021

• 55 Article
• 42 Conference contribution
• 7 Paper
• 3 Chapter
• 6 More
  • 2 Conference article
  • 2 Working paper
  • 1 Meeting abstract
  • 1 Review article

Research output per year

Research output per year

Search results

• Conference contribution

  A Genetic Algorithm with Tree-structured Mutation for Hyperparameter Optimisation of Graph Neural Networks

  Yuan, Y., Wang, W. & Pang, W., 6 Apr 2021, (Accepted/In press) CEC 2021: IEEE Congress on Evolutionary Computation. IEEE

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

• A Hexagonal Cell Automaton Model to Imitate Physarum Polycephalum Competitive Behaviour

  Awad, A., Pang, W., Lusseau, D. & Coghill, G. M., Jul 2019, ALIFE 2019: The 2019 Conference on Artificial Life. MIT Press, p. 203-210 8 p. (Artificial Life Conference Proceedings; no. 31).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Cellular automata
  • Multiobjective optimization
  • Brain
  • Wireless sensor networks
  • Mathematical models
  10 Downloads (Pure)

• A Multi-Modal Deep Learning approach to the Early Prediction of Mild Cognitive Impairment Conversion to Alzheimer’s Disease

  Rana, S. S., Ma, X., Pang, W. & Wolverson, E., 23 Oct 2020, (Accepted/In press) 2020 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT). IEEE, 9302550

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Deep Learning
  • Cognitive Dysfunction
  • Alzheimer Disease
  • Neuroimaging
  • Cognition

• An Evolution Computation Based Approach to Synthesize Video Texture

  Meng, Y., Li, W., Wang, Y., Guo, W. & Pang, W., 5 Dec 2006, Computational Science – ICCS 2006: 6th International Conference, Reading, UK, May 28-31, 2006. Proceedings, Part II. Alexandrov, V. N., van Albada, G. D., Sloot, P. M. A. & Dongarra, J. (eds.). Springer Heidelberg, p. 223-230 8 p. (Lecture Notes in Computer Science ; vol. 3992).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Textures
  • Computer graphics
  • Computer vision
  • Image processing

• An Immune-Inspired Approach to Qualitative System Identification of the Detoxification Pathway of Methylglyoxal

  Pang, W. & Coghill, G. M., 2009, ICARIS 2009: Artificial Immune Systems. Andrews, P. S. (ed.). Springer, p. 151-164 14 p. (Lecture Notes in Computer Science; vol. 5666).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Detoxification
  • Identification (control systems)
  • Learning systems
  • Scalability
  1 Citation (Scopus)

• An immune network approach to learning qualitative models of biological pathways

  Pang, W. & Coghill, G. M., 2014, 2014 IEEE Congress on Evolutionary Computation (CEC). 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Detoxification
  • Antibodies
  • Model checking
  • Differential equations
  1 Citation (Scopus)

• A Novel Diversity Measure for Understanding Movie Ranks in Movie Collaboration Networks

  Ma, M., Pang, W., Huang, L. & Wang, Z., 2017, PAKDD 2017: Advances in Knowledge Discovery and Data Mining . Kim, J., Shim, K., Cao, L., Lee, J-G., Lin, X. & Moon, Y-S. (eds.). Springer, p. 750-761 12 p. (Lecture Notes in Computer Science; vol. 10234).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Chemical analysis

• A Novel Spatio-Temporal Data Storage and Index Method for ARM-Based Hadoop Server

  Han, L., Huang, L., Yang, X., Pang, W. & Wang, K., 2016, ICCCS 2016: Cloud Computing and Security. Sun, X., Liu, A., Chao, H-C. & Bertino, E. (eds.). Springer, p. 206-216 11 p. (Lecture Notes in Computer Science; vol. 10039).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Cloud computing
  • Servers
  • Data storage equipment
  • Electric power transmission networks
  • Global positioning system
  2 Citations (Scopus)

• A Physarum-Inspired Competition Algorithm for Solving Discrete Multi-Objective Optimization Problems

  Awad, A., Usman, M., Lusseau, D., Coghill, G. M. & Pang, W., 13 Jul 2019, GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York, USA: Association for Computing Machinery, p. 195-196 2 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Multiobjective optimization
  • Cellular automata
  • Evolutionary algorithms
  1 Citation (Scopus)

• A Systematic Comparison Study on Hyperparameter Optimisation of Graph Neural Networks for Molecular Property Prediction

  Yuan, Y., Wang, W. & Pang, W., 26 Mar 2021, (Accepted/In press) GECCO 2021: The Genetic and Evolutionary Computation Conference. Association for Computing Machinery

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

• Automatically Predicting Quiz Difficulty Level Using Similarity Measures

  Lin, C., Liu, D., Pang, W. & Apeh, E., Oct 2015, K-CAP 2015: Proceedings of the 8th International Conference on Knowledge Capture. Association for Computing Machinery, 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Linked data
  • Data description
  • Semantics
  • Experiments
  2 Citations (Scopus)

• CLEMI-imputation evaluation

  Chapman, A., Pang, W. & Coghill, G., 23 Aug 2018, 2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI). IEEE, 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Machine learning
  • Testing

• DeepSwarm: Optimising Convolutional Neural Networks using Swarm Intelligence

  Byla, E. & Pang, W., 30 Aug 2019, (E-pub ahead of print) Advances in Computational Intelligence Systems. UKCI 2019. . Ju, Z., Yang, L., Yang, C., Gegov, A. & Zhou, D. (eds.). Springer, p. 119-130 12 p. (Advances in Intelligent Systems and Computing; vol. 1043).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Swarm intelligence
  • Ant colony optimization
  • Neural networks
  • Reusability
  • Deep learning
  5 Citations (Scopus)

• Essential protein identification based on essential protein-protein interaction prediction by integrated edge weights

  Jiang, Y., Wang, Y., Pang, W., Chen, L., Sun, H., Liang, Y. & Blanzieri, E., Jan 2015, 2014 IEEE International Conference on Bioinformatics and Biomedicine. IEEE, 4 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Evolutionary Learning for Soft Margin Problems: A Case Study on Practical Problems with Kernels

  Wang, W., Pang, W., Bingham, P. A., Mania, M., Chen, T-Y. & Perry, J. J., 3 Sep 2020, 2020 IEEE Congress on Evolutionary Computation (CEC). IEEE, 9185574

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Glass
  • Polymers
  • Gradient methods
  • Analysis of variance (ANOVA)
  • Support vector machines
  20 Downloads (Pure)

• Extended kernel subset analysis for qualitative model learning

  Pang, W. & Coghill, G. M., 2012, 2012 12th UK Workshop on Computational Intelligence (UKCI). 7 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Testbeds
  • Experiments
  • Set theory

• FdDCA: A Novel Fuzzy Deterministic Dendritic Cell Algorithm

  Mukhtar, N., Coghill, G. M. & Pang, W., 20 Jul 2016, GECCO '16 Companion: Proceedings of the 2016 on Genetic and Evolutionary Computation Conference. Association for Computing Machinery, p. 1007–1010 4 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Dendritic Cells
  • Immune system
  • K-means clustering
  • Fuzzy sets
  • Fuzzy inference

• Fuzzy discrete particle swarm optimization for solving traveling salesman problem

  Pang, W., Wang, K., Zhou, C. & Dong, L., 30 Nov 2004, Fourth International Conference on Computer and Information Technology, 2004. IEEE, 5 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Traveling salesman problem
  • Particle swarm optimization (PSO)
  • Combinatorial optimization
  • Mathematical operators
  • Computational complexity

• Fuzzy qualitative simulation with multivariate constraints

  Pang, W. & Coghill, G. M., 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Experiments

• Gravitation Field Algorithm with Optimal Detection for Unconstrained Optimization

  Huang, L., Hu, X., Wang, Y., Zhang, F., Liu, Z. & Pang, W., 8 Jan 2018, 2017 4th International Conference on Systems and Informatics (ICSAI). IEEE, p. 1328-1333 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Gravitation
  • Astronomy
  • Planets
  • Dust
  • Particle swarm optimization (PSO)
  1 Citation (Scopus)

  7 Downloads (Pure)

• Hete-CF: Social-Based Collaborative Filtering Recommendation using Heterogeneous Relations

  Luo, C., Pang, W., Wang, Z. & Lin, C., 29 Jan 2015, 2014 IEEE International Conference on Data Mining. 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Collaborative filtering
  52 Citations (Scopus)

• Inferring Structure and Parameters of Dynamic Systems using Latin Hypercube Sampling Multi Dimensional Uniformity-Particle Swarm Optimization

  Usman, M., Awad, A., Pang, W. & Coghill, G. M., 13 Jul 2019, GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York, USA: Association for Computing Machinery, p. 101-102 2 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Particle swarm optimization (PSO)
  • Dynamical systems
  • Sampling
  • Time series
  • Costs
  1 Citation (Scopus)

• Large Margin Distribution Machine Recursive Feature Elimination

  Ou, G., Wang, Y., Pang, W. & Coghill, G. M., 8 Jan 2018, 2017 4th International Conference on Systems and Informatics (ICSAI). IEEE, p. 1518-1523 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Feature extraction
  • Experiments
  5 Citations (Scopus)

• Learning Qualitative Metabolic Models Using Evolutionary Methods

  Pang, W. & Coghill, G. M., 2010, 2010 Fifth International Conference on Frontier of Computer Science and Technology. IEEE, 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Evolutionary algorithms
  • Genetic algorithms
  • Engines
  2 Citations (Scopus)

• Mode-Driven Volume Analysis Based on Correlation of Time Series

  Jia, C., Pang, W. & Fu, Y., 19 Mar 2015, ECCV 2014: Computer Vision - ECCV 2014 Workshops. Agapito, L., Bronstein, M. M. & Rother, C. (eds.). Springer, p. 818-833 16 p. (Lecture Notes in Computer Science; vol. 8925).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Tensors
  • Time series
  • Discriminant analysis
  • Face recognition
  • Experiments
  1 Citation (Scopus)

• Modified clonal selection algorithm for learning qualitative compartmental models of metabolic systems

  Pang, W. & Coghill, G. M., 2007, GECCO '07: Proceedings of the 9th annual conference companion on Genetic and evolutionary computation. Association for Computing Machinery, p. 2887–2894 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Antibodies
  • Set theory
  12 Citations (Scopus)

• Modified particle swarm optimization based on space transformation for solving traveling salesman problem

  Pang, W., Wang, K., Zhou, C., Dong, L., Liu, M., Zhang, H. & Wang, J., Jan 2005, Proceedings of 2004 International Conference on Machine Learning and Cybernetics. IEEE, 5 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Traveling salesman problem
  • Particle swarm optimization (PSO)

• Multi-agent ERA Model Based on Belief Solves Multi-port Container Stowage Problem

  Liu, Y., Wang, K., Guo, D., Pang, W. & Zhou, C., Nov 2008, 2008 Seventh Mexican International Conference on Artificial Intelligence. IEEE, 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Containers
  • Time series
  • Machine learning

• Particle swarm optimization for traveling salesman problem

  Wang, K., Huang, L., Zhou, C. & Pang, W., 21 Jan 2004, Proceedings of the 2003 International Conference on Machine Learning and Cybernetics. IEEE, 3 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Traveling salesman problem
  • Particle swarm optimization (PSO)
  • Experiments

• Partitioning Clustering Based on Support Vector Ranking

  Peng, Q., Wang, Y., Ou, G., Tian, Y., Huang, L. & Pang, W., 2016, ADMA 2016: Advanced Data Mining and Applications. Li, J., Li, X., Wang, S., Li, J. & Sheng, Q. Z. (eds.). Springer International Publishing, p. 726-737 12 p. (Lecture Notes in Computer Science; vol. 10086).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Sorting
  • Clustering algorithms
  • Costs

• Physarum Inspired Connectivity and Restoration for Wireless Sensor and Actor Networks

  Awad, A., Pang, W. & Coghill, G. M., 2018, UKCI 2018: Advances in Computational Intelligence Systems. Lotfi, A., Bouchachia, H., Gegov, A., Langensiepen, C. & McGinnity, M. (eds.). Springer, p. 327-338 12 p. (Advances in Intelligent Systems and Computing; vol. 840).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Restoration
  • Wireless sensor networks
  • Sensors
  • Internet of things
  • Base stations
  1 Citation (Scopus)

• Physarum Inspired Model for Mobile Sensor Nodes Deployment in the Presence of Obstacles

  Awad, A., Pang, W. & Coghill, G., 2018, iCETiC 2018: Emerging Technologies in Computing. Miraz, M. H., Excell, P., Ware, A., Soomro, S. & Ali, M. (eds.). Springer, p. 153-160 8 p. ( Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; vol. 200).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Sensor nodes
  • Sensors
  • Wireless sensor networks
  1 Citation (Scopus)

• PUEPro: A Computational Pipeline for Prediction of Urine Excretory Proteins

  Wang, Y., Du, W., Liang, Y., Chen, X., Zhang, C., Pang, W. & Xu, Y., 2016, ADMA 2016: Advanced Data Mining and Applications . Li, J., Li, X., Wang, S., Li, J. & Sheng, Q. Z. (eds.). Springer International Publishing, p. 714-725 12 p. ( Lecture Notes in Computer Science ; vol. 10086).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Pipelines
  • Proteins
  • Biomarkers
  • Websites
  1 Citation (Scopus)

• QML-AiNet: An Immune-inspired Network Approach to Qualitative Model Learning

  Pang, W. & Coghill, G. M., 2010, ICARIS 2010: Artificial Immune Systems. Hart, E., McEwan, C., Timmis, J. & Hone, A. (eds.). Springer Heidelberg, p. 223-236 14 p. ( Lecture Notes in Computer Science; vol. 6209).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Learning systems
  7 Citations (Scopus)

• Semi-supervised clustering on heterogeneous information networks

  Luo, C., Pang, W. & Wang, Z., May 2014, PAKDD 2014: Advances in Knowledge Discovery and Data Mining . Tseng, V. S., Ho, T. B., Zhou, Z-H., Chen, A. L. P. & Kao, H-Y. (eds.). Springer, p. 548-559 12 p. (Lecture Notes in Computer Science; vol. 8444).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
  19 Citations (Scopus)

• Stepwise modelling of biochemical pathways based on qualitative model learning

  Wu, Z., Pang, W. & Coghill, G. M., 2013, 2013 13th UK Workshop on Computational Intelligence (UKCI). 7 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Biochemistry
  • Topology
  • Chemical analysis
  1 Citation (Scopus)

• Swarm Inspired Approaches for K-prototypes clustering

  Albalawi, H., Pang, W. & Coghill, G. M., 30 Aug 2019, (E-pub ahead of print) Advances in Computational Intelligence Systems. UKCI 2019. . Ju, Z., Yang, L., Yang, C., Gegov, A. & Zhou, D. (eds.). Springer, p. 201-209 9 p. ( Advances in Intelligent Systems and Computing; vol. 1043).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Clustering algorithms
  • Machine learning
  • Data mining

• TCPModel: A Short-Term Traffic Congestion Prediction Model Based on Deep Learning

  Xu, X., Gao, X., Xu, Z., Zhao, X., Pang, W. & Zhou, H., 2019, Artificial Intelligence: ICAI 2019. Singapore: Springer, p. 66-79 14 p. (Communications in Computer and Information Science; vol. 1001).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Traffic congestion
  • Deep learning
  • Spatial distribution
  1 Citation (Scopus)

• Towards a Robust Imputation Evaluation Framework

  Chapman, A., Pang, W. & Coghill, G., 24 Jun 2018, Proceedings of The Seventh International Conference on Intelligent Systems and Applications. IARIA, p. 7-13 7 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Machine learning
  • Testing

• Towards making NLG a voice for interpretable Machine Learning

  Forrest, J., Sripada, S., Pang, W. & Coghill, G., Nov 2018, Proceedings of the 11th International Conference on Natural Language Generation. Association for Computational Linguistics, p. 177–182 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • learning
  • comprehension
  • rating

• Towards Real-Time Detection of Squamous PreCancers from Oesophageal Endoscopic Videos

  Gao, X., Braden, B., Taylor, S. & Pang, W., 7 Oct 2019, (Accepted/In press) 2019 18th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Epithelial Cells
  • Masks
  • Deep learning
  • Graphics processing unit
  • Pixels
  33 Downloads (Pure)

• ε-Distance Weighted Support Vector Regression

  Ou, G., Wang, Y., Huang, L., Pang, W. & Coghill, G. M., 2018, PAKDD 2018: Advances in Knowledge Discovery and Data Mining. Phung, D., Tseng, V. S., Webb, G. I., Ho, B., Ganji, M. & Rashidi, L. (eds.). Springer, p. 209-220 ( Lecture Notes in Artificial Intelligence ; vol. 10937).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
  2 Citations (Scopus)