|Name||Dr. Shuxiang Xu|
|Qualifications||BSc, MSc, PhD (Western Sydney)|
|Phone||(03) 6324 3416|
|Lecturing||KIT108 - Artificial Intelligence|
|About Me||My research interests include Artificial Intelligence (Artificial Neural Network, Genetic Algorithm, etc), Machine Learning, and Data Mining.
My UTAS Individual Researchers Report shows information about my current PhD supervision etc
Individual Researchers Report on WARP
The following are some of my recent publications:
Kabir MMJ, Xu S, Kang BH, Zhao Z (2017), A new multiple seeds based genetic algorithm for discovering a set of interesting Boolean association rules, Expert Systems with Applications, Volume 74, 15 May 2017, Pages 55-69.
Zhao, Z and Xu, S and Kang, BH and Kabir, MMJ and Liu, Y and Wasinger, R (2015), Investigation and improvement of multi-layer perceptron neural networks for credit scoring, Expert Systems With Applications, 42 (7) pp. 3508-3516.
Kabir MMJ, Xu S, Kang BH, Zhao Z (2014), A Hybrid GeneticMax Algorithm for Improving the Traditional Genetic Based Approach for Mining Maximal Frequent Item Sets, IJCSNS International Journal of Computer Science and Network Security, VOL.14 No.10, pp. 27-35.
Zhao Z, Xu S, Kang BH, Kabir MMJ, Liu Y (2014), Investigation of Multilayer Perceptron and Class Imbalance Problems for Credit Rating, International Journal of Computer and Information Technology, Volume 03, Issue 04, pp. 805-812.
Kabir MMJ, Xu S, Kang BH, Zhao Z (2014), Association Rule Mining for Both Frequent and Infrequent Items Using Particle Swarm Optimization Algorithm, International Journal on Computer Science and Engineering, Vol 6, No07, pp. 221-231.
Xu S, Liu Y (2014), Neural Networks for Business Decision Making, International Journal of Advancements in Computing Technology, Volume 6, Number 2, pages 49-58.
Xu S (2010), "Data Mining Using Higher Order Neural Network Models With Adaptive Neuron Activation Functions", IJACT : International Journal of Advancements in Computing Technology, Vol. 2, No. 4, pp. 168 ~ 177.
Zhang M, Xu S, and Fulcher J (2007), ANSER: an Adaptive-Neuron Artificial Neural Network System for Estimating Rainfall Using Satellite Data. International Journal of Computers and Applications. Vol. 29. No. 3. 2007. pp. 215-222.
Zhang M, Xu S, Fulcher J (2002), Neuron-Adaptive Higher Order Neural Network Models for Financial Data Auto-modeling, IEEE Transactions on Neural Networks, VOL13, NO1, pp.188-204.
Xu, S and Liu, Y (2016), A Theoretical Framework for Parallel Implementation of Deep Higher Order Neural Networks, Applied Artificial Higher Order Neural Networks for Control and Recognition, Information Science Reference, M Zhang (ed), Hershey PA, USA, pp. 351-361. ISBN 9781522500636.
Zhao, Z and Xu, S and Kang, BH and Kabir, MMJ and Liu, Y and Wasinger, R (2016), Utilizing Feature Selection on Higher Order Neural Networks, Applied Artificial Higher Order Neural Networks for Control and Recognition, Information Science Reference, M Zhang (ed), Hershey PA, USA, pp. 375-390. ISBN 9781522500636.
Xu S (2012), Chapter 13: HONNs with Extreme Learning Machine to Handle Incomplete Datasets, Artificial Higher Order Neural Networks for Modeling and Simulation, Zhang M (editor), IGI Global, ISBN: 978-1-4666-2175-6, pp 276-292.
Xu S (2010), Chapter 4: Adaptive Higher Order Neural Network Models For Data Mining, Artificial Higher Order Neural Networks for Computer Science and Engineering, Zhang M (ed), IGI Global, ISBN: 978-161692251-1, pp 86-98.
Xu S (2009), Chapter XIV: Adaptive Higher Order Neural Network Models and Their Applications in Business, Artificial Higher Order Neural Networks for Economics and Business, Zhang M (ed), IGI Global, ISBN: 978-1-59904-897-0, pp 314 ? 329.
Fulcher J, Zhang M, Xu S (2006) Chapter V. Application of Higher-Order Neural Networks to Financial Time-Series Prediction, Artificial Neural Networks in Finance and Manufacturing, edited by Joarder Kamruzzaman, Rezaul Begg, and Ruhul Sarker, Idea Group Publishing, ISBN: 1591406714, pp. 80-108.
Kabir, MMJ and Xu, S and Kang, BH and Zhao, Z (2015), A new evolutionary algorithm for extracting a reduced set of interesting association rules, Neural Information Processing 22nd International Conference, ICONIP 2015, Proceedings, Part II, 09-12 November, Istanbul, Turkey, pp. 133-142. ISBN 978-3-319-26534-6.
Kabir, MMJ and Xu, S and Kang, BH and Zhao, Z (2015), Comparative analysis of genetic based approach and apriori algorithm for mining maximal frequent item sets, Proceedings of the 2015 IEEE Congress on Evolutionary Computation, 25-28 May 2015, Sendai, Japan, pp. 39-45. ISBN 978-1-4799-7492-4.
Zhao Z, Xu S, Kang BH, Kabir MMJ, Liu Y (2014), Instance Selection and Optimization of Neural Networks, The 9th International Conference on Information Technology and Applications (ICITA2014), 1 - 4 July, 2014, Sydney, Australia. CD-ROM proceedings online at: http://www.icita.org/2014/CD/home.htm
Kabir MMJ, Xu S, Kang BH, Zhao Z (2014), A Novel Approach to Mining Maximal Frequent Itemsets Based on Genetic Algorithm, The 9th International Conference on Information Technology and Applications (ICITA2014), 1 - 4 July, 2014, Sydney, Australia. CD-ROM proceedings online at: http://www.icita.org/2014/CD/home.htm
Xu S, Liu Y, Kang BH, Gao W (2013), A Machine Learning Approach for Modeling and Its Applications, Proceedings of the 25th European Modeling and Simulation Symposium, September 25-27 2013, Athens, Greece, pp 659-663.
Xu S, Liu YL (2012), HONNs With ELM Algorithm for Medical Applications, Proceedings of ICARCV 2012 (12th International Conference on Control, Automation, Robotics and Vision, Guangzhou, China in 5~7 December 2012), pp 1215-1219.
Xu, S (2011), An Extreme Learning Machine Algorithm for Higher Order Neural Network Models, Proceedings of EMSS2011, Rome, Italy, 12-14 Sept 2011, pp 418-422.
Xu, S (2010), Data Mining Using an Adaptive HONN Model with Hyperbolic Tangent Neurons, Proceedings of the 11th International Workshop on Knowledge Management and Acquisition for Smart Systems and Services (PKAW2010), Daegu, Korea, August 30-31 2010, pp 73-81, ISBN 978-3-642-15036-4.
Xu, S (2010), Features of Higher Order Neural Network With Adaptive Neurons, Proceeding of the 2nd International Conference on Software Engineering and Data Mining (SEDM2010), 23-25 June 2010, Chengdu, P.R. China, pp. 484-488. ISBN 978-89-88678-22-0.
Xu, S (2009), A Novel Higher Order Artificial Neural Networks, Proceedings of the Second International Symposium on Computational Mechanics (ISCM II), 30 Nov - 3 Dec 2009, Hong Kong-Macau, pp. 1507-1511. ISBN: 978-0-7354-0778-7.
Xu S, Chen L (2009), Adaptive Higher Order Neural Networks for Effective
Data Mining, Proceedings of The Sixth International Symposium on Neural Networks (ISNN 2009), Wuhan, China, May 26-29, 2009, pp 165 ? 173.
Xu S, Chen L (2009), Adaptive Higher Order Neural Networks, Proceedings of 2009 Global Congress on Intelligent Systems, Xiamen, China, May 19-21, 2009, pp 26-30.
Xu, S and Chen, L (2008), A novel approach for determining the optimal number of hidden layer neurons for FNN's and its application in data mining, Proceedings The 5th International Conference on Information Technology and Applications, 23-26 June 2008, Carins, Qld, pp. 683-686. ISBN 978-0-9803267-2-7
Authorised by the Head of School, Engineering & ICT
14 June, 2012