Wenjia Wang

Search results

• 2024

  Heterogeneous machine learning ensembles for predicting train delays

  Al Ghamdi, M., Parr, G. & Wang, W., Jun 2024, In: IEEE Transactions on Intelligent Transportation Systems. 25, 6, p. 5138-5153 16 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  1 Citation (Scopus)

  23 Downloads (Pure)

• Quantitative and qualitative similarity measure for data clustering analysis

  AlShaqsi, J., Wang, W., Drogham, O. & Alkhawaldeh, R. S., Dec 2024, In: Cluster Computing. 27, 10, p. 14977-15002 26 p.

  Research output: Contribution to journal › Article › peer-review

• Tri-level robust clustering ensemble (TRCE) algorithm for clustering enhancement with comparative analysis

  Alshaqsi, J., Wang, W. & Drogham, O., 9 Aug 2024, In: Engineered Science. 30, 13 p.

  Research output: Contribution to journal › Article › peer-review
• 2023

  Novel methods for imputing missing values in water level monitoring data

  Khampuengson, T. & Wang, W., Jan 2023, In: Water Resources Management. 37, 2, p. 851-878 28 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  13 Citations (Scopus)

  37 Downloads (Pure)
• 2022

  Creating Variant Features to Enhance Covid-19 Predictions with Machine Learning Ensemble

  Wood, J. & Wang, W., 21 Jan 2022, Preprints.org.

  Research output: Working paper › Preprint

  Open Access

• Decision level ensemble method for classifying multi-media data

  Alyahyan, S. & Wang, W., Apr 2022, In: Wireless Networks. 28, 3, p. 1219–1227 9 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  3 Citations (Scopus)

  57 Downloads (Pure)

• Deep reinforcement learning ensemble for detecting anomaly in telemetry water level data

  Khampuengson, T. & Wang, W., 13 Aug 2022, In: Water. 14, 16, 2492.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  5 Citations (Scopus)

  31 Downloads (Pure)

• Detecting the Faults of Subsea Power Cables of Wind Farms with Boosting Ensemble Methods

  Eze, O., Guile, G. & Wang, W., Nov 2022, Proceedings of the International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME). ICECCME, p. 2492-2497 6 p.

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

  Open Access

  File
  19 Downloads (Pure)

• The Potential of Artificial Intelligence in Phase-Measuring Bathymetric Sonar Data Processing

  Milner, B., Wang, W., Websdale, D., Gutierrez, F. & Dowdeswell, R., 1 Apr 2022.

  Research output: Contribution to conference › Paper › peer-review
• 2020

  Developing Ensemble Methods for Detecting Anomalies in Water Level Data

  Khampuengson, T., Bagnall, T. & Wang, W., 8 Dec 2020, The 22nd International Conference on Big Data Analytics and Knowledge Discovery. Bramer, M. & Ellis, R. (eds.). Springer, p. 145-151 7 p.

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

  Open Access

  File
  1 Citation (Scopus)

  26 Downloads (Pure)

• Multiple Imputation Ensembles (MIE) for dealing with missing data

  Aleryani, A., Wang, W. & De La Iglesia, B., May 2020, In: SN Computer Science. 1, 3, 134.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  25 Citations (Scopus)

  71 Downloads (Pure)

• Weighted Ensemble Methods for Predicting Train Delays

  Al Ghamdi, M., Parr, G. & Wang, W., 1 Oct 2020, Computational Science and Its Applications – ICCSA 2020 - 20th International Conference, Proceedings. Gervasi, O., Murgante, B., Misra, S., Garau, C., Blecic, I., Taniar, D., Apduhan, B. O., Rocha, A. M. A. C., Tarantino, E., Torre, C. M. & Karaca, Y. (eds.). 978-3-030-58798-7, p. 586-600 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12249 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
  1 Citation (Scopus)
• 2019

  Clustering ensemble method

  Alqurashi, T. & Wang, W., 1 Jun 2019, In: International Journal of Machine Learning and Cybernetics. 10, 6, p. 1227-1246 20 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  84 Citations (Scopus)

  39 Downloads (Pure)

• Hybrid expert ensembles for identifying unreliable data in citizen science

  Wessels, P., Moran, N., Johnston, A. & Wang, W., May 2019, In: Engineering Applications of Artificial Intelligence. 81, p. 200-212 13 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  4 Citations (Scopus)

  17 Downloads (Pure)

• Hybrid Feature Selection Method for Improving File Fragment Classification

  Algurashi, A. & Wang, W., 2019, Artificial Intelligence XXXVI - 39th SGAI International Conference on Artificial Intelligence, AI 2019, Proceedings. Bramer, M. & Petridis, M. (eds.). p. 379-391 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11927 LNAI).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 2018

  Automatic Counting of Wheat Spikes from Wheat Growth Images

  Alharbi, N., Zhou, J. & Wang, W., 17 Jan 2018, 7th International Conference on Pattern Recognition Applications and Methods. SciTePress – Science and Technology Publications, p. 346-355 10 p.

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

  Open Access

  File
  24 Citations (Scopus)

  107 Downloads (Pure)

• Dealing with Missing Data and Uncertainty in the Context of Data Mining

  Aleryani, A., Wang, W. & De La Iglesia, B., 2018, Hybrid Artificial Intelligent Systems: 13th International Conference, HAIS 2018, Oviedo, Spain, June 20-22, 2018, Proceedings. Springer, p. 289-301 13 p. (Hybrid Artificial Intelligent Systems; vol. 10870).

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

  Open Access

  File
  11 Citations (Scopus)

  126 Downloads (Pure)

• Generalised Decision Level Ensemble Method for Classifying Multi-media Data

  Alyahyan, S. & Wang, W., Dec 2018, SGAI 2018: Artificial Intelligence XXXV. Springer, p. 326-339

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

  Open Access

  File
  26 Downloads (Pure)
• 2017

  Determining appropriate approaches for using data in feature selection

  Aldehim, G. & Wang, W., Jun 2017, In: International Journal of Machine Learning and Cybernetics. 8, 3, p. 915–928

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  29 Citations (Scopus)

  18 Downloads (Pure)

• Feature Level Ensemble Method for Classifying Multi-Media Data

  Alyahyan, S. & Wang, W., 21 Nov 2017, International Conference on Innovative Techniques and Applications of Artificial Intelligence: SGAI 2017: Artificial Intelligence XXXIV. Bramer, M. & Petridis, M. (eds.). Springer, p. 235-249 13 p. (Lecture Notes in Computer Science; vol. 10630).

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

  Open Access

  File
  2 Citations (Scopus)

  28 Downloads (Pure)
• 2016

  Dynamic ensemble selection methods for heterogeneous data mining

  Ballard, C. & Wang, W., 29 Sep 2016, 12th World Congress on Intelligent Control and Automation (WCICA), 2016. The Institute of Electrical and Electronics Engineers (IEEE)

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

  Open Access

  File
  18 Citations (Scopus)

  20 Downloads (Pure)

• Heterogeneous Ensemble for Imaginary Scene Classification

  Alyahyan, S., Farrash, M. & Wang, W., 2016, Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR. p. 197-204 8 p.

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

  Open Access

  File
  5 Citations (Scopus)

  28 Downloads (Pure)
• 2015

  An Algorithm for Identifying the Learning Patterns in Big Data

  Farrash, M. & Wang, W., 20 Aug 2015, p. 48-55. 8 p.

  Research output: Contribution to conference › Paper › peer-review

  1 Citation (Scopus)

• A New Consensus Function based on Dual-Similarity Measurements for Clustering Ensemble

  Alqurashi, T. & Wang, W., Oct 2015.

  Research output: Contribution to conference › Paper › peer-review

  10 Citations (Scopus)

• Applying Clustering Analysis to Heterogeneous Data Using Similarity Matrix Fusion (SMF)

  Mojahed, A., Bettencourt-Silva, J. H., Wang, W. & de la Iglesia, B., 2015, Machine Learning and Data Mining in Pattern Recognition: 11th International Conference, MLDM 2015, Hamburg, Germany, July 20-21, 2015, Proceedings. Perner, P. (ed.). Springer, Vol. 9166. p. 251-265 15 p. (Lecture Notes in Computer Science).

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

• Autoimmune hemolytic anemia after allogeneic hematopoietic stem cell transplantation: Analysis of 533 adult patients who underwent transplantation at King’s College Hospital

  Wang, M., Wang, W., Abeywardane, A. & Mijovic, A., Jan 2015, In: Biology of Blood and Marrow Transplantation. 21, 1, p. 60-66 7 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  58 Citations (Scopus)

• Comparative performance of Texton based vascular tree segmentation in retinal images

  Zhang, L., Fisher, M. & Wang, W., 29 Jan 2015, 2014 IEEE International Conference on Image Processing (ICIP). The Institute of Electrical and Electronics Engineers (IEEE), p. 952-956 5 p.

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

• Modelling the role of catastrophe, crossover and Katanin in the self organisation of cortical microtubules

  Mace, A. & Wang, W., Dec 2015, In: IET Systems Biology. 9, 6, p. 277-284 8 p.

  Research output: Contribution to journal › Article › peer-review
  4 Citations (Scopus)

• Retinal vessel segmentation using multi-scale textons derived from keypoints

  Zhang, L., Fisher, M. & Wang, W., Oct 2015, In: Computerized Medical Imaging and Graphics. 45, p. 47-56 10 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  59 Citations (Scopus)

  19 Downloads (Pure)

• Weighted Heuristic Ensemble of Filters

  Aldehim, G. & Wang, W., 10 Nov 2015, p. 609-615. 7 p.

  Research output: Contribution to conference › Paper › peer-review

  Open Access

  File
  3 Citations (Scopus)

  14 Downloads (Pure)
• 2014

  A Graph based Methodology for Web Structure Mining: with a Case Study on the Webs of UK Universities

  Alqurashi, T. & Wang, W., Jun 2014.

  Research output: Contribution to conference › Paper › peer-review

• A Texture Analysis Approach to Identifying Sabellaria Spinulosa Colonies in Sidescan Sonar Imagery

  Harrison, R., Bianconi, F., Harvey, R. & Wang, W., 24 Nov 2014, 2011 Irish Machine Vision and Image Processing Conference. The Institute of Electrical and Electronics Engineers (IEEE)

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

• Heuristic Ensemble of Filters for Reliable Feature Selection

  Aldehim, G., De La Iglesia, B. & Wang, W., May 2014.

  Research output: Contribution to conference › Paper › peer-review

  2 Citations (Scopus)

• Object-Neighbourhood based Clustering Ensemble Method

  Alqurashi, T. & Wang, W., 10 Sep 2014.

  Research output: Contribution to conference › Paper › peer-review

• Reliability and Effectiveness of Cross-validation in Feature Selection

  Aldehim, G. & Wang, W., Dec 2014, p. 179-184. 6 p.

  Research output: Contribution to conference › Paper › peer-review

• Retinal vessel segmentation using Gabor Filter and Textons

  Zhang, L., Fisher, M. & Wang, W., 2014, p. 155-160. 6 p.

  Research output: Contribution to conference › Paper › peer-review

  File
  50 Citations (Scopus)

  15 Downloads (Pure)
• 2013

  A Hybrid Method for Estimating the Predominant Number of Clusters in a Data Set

  Alshaqsi, J. & Wang, W., 11 Jan 2013, Proceedings of the 11th International Conference on Machine Learning and Applications (ICMLA). The Institute of Electrical and Electronics Engineers (IEEE)

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

• Autoimmune haemolytic anaemia after allogeneic haematopoietic stem cell transplantation: analysis of 555 transplant patients at King’s College Hospital

  Wang, M., Wang, W. & Abeywardane, A., Apr 2013.

  Research output: Contribution to conference › Paper › peer-review

• Estimating the predominant number of clusters in a dataset

  Al Shaqsi, J. & Wang, W., Jul 2013, In: Intelligent Data Analysis. 17, 4, p. 603-626 24 p.

  Research output: Contribution to journal › Article › peer-review
  4 Citations (Scopus)

• How data partitioning strategies influence the performance of ensemble in big data mining?

  Wang, W. & Farrash, M., Oct 2013.

  Research output: Contribution to conference › Paper › peer-review

• Locating blood vessels in retinal images using unified Textons

  Zhang, L., Fisher, M. & Wang, W., Jul 2013, p. 213-218. 6 p.

  Research output: Contribution to conference › Paper › peer-review
• 2012

  Non-linear dimensionality reduction for privacy-preserving data classification

  Alotaibi, K., Rayward-Smith, V. J., Wang, W. & De La Iglesia, B., 2012, Proceedings - 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust and 2012 ASE/IEEE International Conference on Social Computing, SocialCom/PASSAT 2012. p. 694-701 8 p.

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

• Novel consensus approaches to the reliable ranking of features for seabed imagery classification

  Harrison, R., Birchall, R., Mann, D. & Wang, W., Dec 2012, In: International Journal of Neural Systems. 22, 6, 18 p., 1250026.

  Research output: Contribution to journal › Article › peer-review
  7 Citations (Scopus)

• Objective and subjective measures of fuel poverty

  Waddams Price, C., Brazier, K. & Wang, W., Oct 2012, In: Energy Policy. 49, p. 33-39 7 p.

  Research output: Contribution to journal › Article › peer-review
  149 Citations (Scopus)

• What influences the accuracy of decision tree ensembles?

  Richards, G. & Wang, W., Dec 2012, In: Journal of Intelligent Information Systems. 39, 3, p. 627-650 24 p.

  Research output: Contribution to journal › Article › peer-review
  10 Citations (Scopus)
• 2011

  Adaptive K-Means for Clustering Air Mass Trajectories

  Mace, A., Sommariva, R., Fleming, Z. & Wang, W., 2011, Intelligent Data Engineering and Automated Learning - IDEAL 2011. Yin, H., Wang, W. & Rayward-Smith, V. (eds.). Springer, p. 1-8 8 p.

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

• A Novel Ensemble of Distance Measures for Feature Evaluation: Application to Sonar Imagery

  Harrison, R., Birchall, R., Mann, D. & Wang, W., 2011, Intelligent Data Engineering and Automated Learning - IDEAL 2011. Yin, H., Wang, W. & Rayward-Smith, V. (eds.). Springer, p. 327-336 10 p.

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

• Classification of household devices by electricity usage profiles

  Lines, J. A., Bagnall, A., Caiger-Smith, P., Anderson, S., Yin, H. (ed.), Wang, W. (ed.) & Rayward-Smith, V. (ed.), 2011, In: Proceedings of the 12th International Conference on Intelligent Data Engineering and Automated Learning. p. 403-412 10 p.

  Research output: Contribution to journal › Conference article › peer-review

  File
  44 Citations (Scopus)

  58 Downloads (Pure)

• Novel Data Mining Approaches for Detecting Quantitative Trait Loci of Bone Mineral Density in Genome-Wide Linkage Analysis

  Li, Q., Macgregor, A. J. & Wang, W., 2011, Intelligent Data Engineering and Automated Learning - IDEAL 2011. Yin, H., Wang, W. & Rayward-Smith, V. (eds.). Springer, p. 498-510 13 p.

  Research output: Chapter in Book/Report/Conference proceeding › Chapter
• 2009

  Degradome expression profiling in human articular cartilage

  Swingler, T. E., Waters, J. G., Davidson, R. K., Pennington, C. J., Puente, X. S., Darrah, C., Cooper, A., Donell, S. T., Guile, G. R., Wang, W. & Clark, I. M., 23 Jun 2009, In: Arthritis Research & Therapy. 11, 96.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  62 Citations (Scopus)