School of Engineering and Computer Science Te Kura Mātai Pūkaha, Pūrorohiko

  • Mirghasemi, S., Rayudu, R., & Zhang, M. (2013) "A new image segmentation algorithm based on modified seeded region growing and particle swarm optimization". In International Conference Image and Vision Computing New Zealand (pp. 382-387). Wellingtn, New Zealand. doi:10.1109/IVCNZ.2013.6727045
  • Marzukhi, S., Browne, W. N., & Zhang, M. (2013) "Adaptive artificial datasets through learning classifier systems for classification tasks". Evolutionary Intelligence, 6(2), 93-107. doi:10.1007/s12065-013-0094-y
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  • Gomes, H. M., & Enembreck, F. (2013) "SAE: Social Adaptive Ensemble classifier for data streams". In Proceedings of the 2013 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013 (pp. 199-206). doi:10.1109/CIDM.2013.6597237
  • Nguyen, S., Zhang, M., Johnston, M., & Chen Tan, K. (2013) "A Computational Study of Representations in Genetic Programming to Evolve Dispatching Rules for the Job Shop Scheduling Problem". IEEE Transactions on Evolutionary Computation, 17(5), 621-639. doi:10.1109/TEVC.2012.2227326
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  • Marzukhi, S., Browne, W. N., & Zhang, M. (2013) "Adaptive artificial datasets to discover the effects of domain features for classification tasks". In GECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference Companion (pp. 157-158). doi:10.1145/2464576.2464654
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  • Xue, B., Cervante, L., Shang, L., Browne, W., & Zhang, M. (2013) "Multi-Objective Evolutionary Algorithms for Filter Based Feature Selection in Classification". International Journal on Artificial Intelligence Tools, 22(4), 1350024-1-1350024-31. doi:10.1142/S0218213013500243
  • Pang, S., Zhu, L., Chen, G., Sarrafzadeh, A., Ban, T., & Inoue, D. (2013) "Dynamic class imbalance learning for incremental LPSVM". Neural Networks, 44, 87-100. doi:10.1016/j.neunet.2013.02.007
  • Nguyen, S., Zhang, M., Johnston, M., & Chen Tan, K. (2013) "Hybrid evolutionary computation methods for quay crane scheduling problems". Computers & Operations Research, 40(8), 2083-2093. doi:10.1016/j.cor.2013.03.007
  • Ma, H., Noack, R., Schewe, K. D., Thalheim, B., & Wang, Q. (2013) "Complete conceptual schema algebras". Fundamenta Informaticae, 124(3), 271-295. doi:10.3233/FI-2013-834
  • Rada-Velila, J., Zhang, M., & Seah, K. (2013) "A performance study on synchronicity and neighborhood size in particle swarm optimization". Soft Computing, 17(6), 1019-1030. doi:10.1007/s00500-013-1015-9
  • Bhowan, U., Johnston, M., Zhang, M., & Yao, X. (2013) "Evolving Diverse Ensembles Using Genetic Programming for Classification With Unbalanced Data". IEEE Transactions on Evolutionary Computation, 17(3), 368-386. doi:10.1109/TEVC.2012.2199119
  • Xue, B., & Ma, W. D. (2013) "Optimization research of cavity milling processing parameters". In Proceedings - 2013 5th Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2013 (pp. 774-776). doi:10.1109/ICMTMA.2013.191
  • Nguyen, S., Zhang, M., Johnston, M., & Tan, K. C. (2013) "Learning reusable initial solutions for multi-objective order acceptance and scheduling problems with genetic programming". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 7831 LNCS (pp. 157-168). doi:10.1007/978-3-642-37207-0_14
  • Cervante, L., Xue, B., Shang, L., & Zhang, M. (2013) "A multi-objective feature selection approach based on binary PSO and rough set theory". In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 7832 LNCS (pp. 25-36). doi:10.1007/978-3-642-37198-1_3
  • Iqbal, M., Browne, W. N., & Zhang, M. (2013) "Evolving optimum populations with XCS classifier systems: XCS with code fragmented action". Soft Computing, 17(3), 503-518. doi:10.1007/s00500-012-0922-5
  • Iqbal, M., Browne, W., & Zhang, M. (2013) "Evolving optimum populations with XCS classifier systems: XCS with code fragmented action". Soft Computing, 17(3), 503-518. doi:10.1007/s00500-012-0922-5
  • Xie, H., & Zhang, M. (2013) "Parent Selection Pressure Auto-Tuning for Tournament Selection in Genetic Programming". IEEE Transactions on Evolutionary Computation, 17(1), 1-19. doi:10.1109/TEVC.2011.2182652
  • Zhang, M., Koeppen, M., & Damas, S. (2013) "Special Issue on Computational Intelligence in Computer Vision and Image Processing [Guest Editorial] (Vol". 8). IEEE: IEEE Computational Intelligence Magazine.
  • Yu, Y., Ma, H., & Zhang, M. (2013) "An Adaptive Genetic Programming Approach to QoS-aware Web Services Composition". In Proceedings of 2013 IEEE Congress on Evolutionary Computation (pp. 1740-1747). IEEE Press.
  • Xue, B., Zhang, M., Dai, Y., & Browne, W. (2013) "PSO for Feature Construction and Binary Classification". In C. Blum (Ed.), GECCO'13 Proceedings of the 2013 Genetic and Evolutionary Computation Conference (pp. 137-144). New York: The Association for Computing Machinery, Inc. (ACM).. Retrieved from https://dl.acm.org/citation.
  • Xue, B., Zhang, M., & Browne, W. N. (2013) "Particle swarm optimization for feature selection in classification: A multi-objective approach". IEEE transactions on cybernetics, 43(6), 1656-1671. doi:10.1109/TSMCB.2012.2227469
  • Xue, B., Zhang, M., & Browne, W. N. (2013) "Novel Initialisation and Updating Mechanisms in PSO for Feature Selection in Classification". In Applications of Evolutionary Computation (pp. 428-438). Springer Berlin Heidelberg. doi:10.1007/978-3-642-37192-9_43
  • Xue, B., Zhang, M., & Browne, W. (2013) "Novel Initialisation and Updating Mechanisms in PSO for Feature Selection in Classification". In Proceedings of the 16th European Conference on Applications of Evolutionary Computation (EvoApplications 2013). Lecture Notes in Computer Science (Vol. 7835, pp. 428-438). Berlin: Springer.
  • Welch, I., Gao, X., Komisarczuk, P., & others. (2013) "Detecting heap-spray attacks in drive-by downloads: Giving attackers a hand". In 38th Annual IEEE Conference on Local Computer Networks (pp. 300-303). IEEE.
  • Wang, A., Ma, H., & Zhang, M. (2013) "Genetic Programming with Greedy Search for Web Service Composition". In Database and Expert Systems Applications (pp. 9-17). Springer-Verlag Berlin Heidelberg.
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  • Thompson, D., Bell, T., Andreae, P., & Robins, A. (2013) "The Role of Teachers in Implementing Curriculum Changes". In Proceeding of the 44th ACM Technical Symposium on Computer Science Education, SIGCSE '13 (pp. 245-250). New York: ACM.
  • Stojmirovic, A., Andreae, P., Boland, M., Jordan, T., Pestov, V., Brisaboa, N., . . . Zezula, P. (2013) "PFMFind: a system for discovery of peptide homology and function". In 6th International Conference, SISAP 2013 (pp. 319-324). doi:10.1007/978-3-642-41062-8_32
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  • Song, L., Pang, S., Chen, G., Sarrafzadeh, H., Ban, T., & Inoue, D. (2013) "An incremental learning approach to continuous image change detection". In Fuzzy Systems and Knowledge Discovery (FSKD), 2013 10th International Conference on (pp. 747-752). Shenyang, China. doi:10.1109/FSKD.2013.6816294
  • Setayeshbarhaghi, M., Zhang, M., & Johnston, M. (2013) "A Novel Particle Swarm Optimisation Approach to Detecting C ontinuous, Thin and Smooth Edges in Noisy Images". Information Sciences, 246, 28-51.
  • Setayeshbarhaghi, M., Johnston, M., & Zhang, M. (2013) "A Novel Particle Swarm Optimisation Approach to Detecting Continuous, Thin and Smooth Edges in Noisy Images". Information Sciences, 246, 28-51.
  • Scoble, A., Zhang, M., Browne, W., Bruce, Z., & Stephenson, B. (2013) "Evolutionary Spatial Auto-Correlation for Assessing Earthquake Liquefaction Potential using Parallel Linear Genetic Programming". In Proceedings of 2013 IEEE Congress on Evolutionary Computation (pp. 2940-2947).
  • Samian, N., Seah, W., & Chen, A. (2013) "Quantifying Selfishness and Fairness in Wireless Multihop Networks". In Proceedings of the 38th Annual IEEE Conference on Local Computer Networks (pp. 1-9). Sydney: IEEE. doi:10.1109/LCN.2013.6761279
  • Roberts, R., Jones, T., & Lewis, J. (2013) "Synthesis of incidental detail as composable components in a functional language". In T. Rhee, R. Rayudu, C. Hollitt, J. Lewis, & M. Zhang (Eds.), Image and Vision Computing New Zealand (IVCNZ), 2013 28th International Conference of (pp. 305-310). Wellington, New Zealand.
  • Rada-Velila, J., Zhang, M., & Johnston, M. (2013) "Resampling in Particle Swarm Optimization". In Proceedings of 2013 IEEE Congress on Evolutionary Computation (pp. 947-954).
  • Rada-Velila, J., Johnston, M., & Zhang, M. (2013) "Optimal Computing Budget Allocation in Particle Swarm Optimization". In Proceedings of 2013 Genetic and Evolutionary Computation Conference. (pp. 81-88).
  • Peng, Y., Pang, S., Chen, G., Sarrafzadeh, A., Ban, T., & Inoue, D. (2013) "Chunk incremental IDR/QR LDA learning". In International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). Washington, DC: IEEE.
  • Nguyen, S., Zhang, M., Johnston, M., & Tan, K. C. (2013) "Dynamic multi-objective job shop scheduling: A genetic programming approach". Studies in Computational Intelligence, 505, 251-282. doi:10.1007/978-3-642-39304-4_10
  • Nguyen, S., Zhang, M., Johnston, M., & Chen Tan, K. (2013) "Learning Reusable Initial Populations for Multi-objective Order Acceptance and Scheduling Problems with Genetic Programming". In Proceedings of the 16th European Conference on Genetic Programming (EuroGP 2013). Lecture Notes in Computer Science (Vol. 7831, pp. 168). Berlin: Springer.
  • Nguyen, S., Zhang, M., Johnston, M., & Chen Tan, K. (2013) "Learning Iterative Dispatching Rules for Job Shop Scheduling with Genetic Programming". Special issue on Advanced Dispatching Rules for Large-scale Manufacturing Systems, International Journal of Advanced Manufacturing Technology, 67(1-4), 85-100.
  • Nguyen, S., Zhang, M., Johnston, M., & Chen Tan, K. (2013) "Hybrid evolutionary computation methods for quay crane scheduling problems Computers & Operations Research". (Journal of) Computers and Operations Research, 40(8), 2083-2093.
  • Nguyen, S., Zhang, M., Johnston, M., & Chen Tan, K. (2013) "Genetic Programming for Evolving Reusable Due-date Assignment Models in Job Shop Environment". Evolutionary Computation (Journal, MIT Press).
  • Nguyen, S., Zhang, M., Johnston, M., & Chen Tan, K. (2013) "A MO-GPHH Approach to Dynamic Job Shop Scheduling Problems". In N. Urquhart, S. Etaner-Uyar, & E. Ozcan (Eds.), Book Chapter on Automated Scheduling, Studies in Computational Intelligence (pp. 251-282). Springer.
  • Mirghasemi, S., Rayudu, R., & Zhang, M. (2013) "A New Image Segmentation Algorithm Based on Modified Seeded Region Growing and Particle Swarm Optimization". In Proceedings of 2013 the 28th International Conference on Image and Vision Computing New Zealand (IVCNZ 2013) (pp. 282-387). IEEE Press.
  • Mirghasemi, S., Rayudu, R., & Zhang, M. (2013) "A feature-based region growing-merging approach to color image segmentation". In Proceedings of 2013 the 28th International Conference on Image and Vision Computing New Zealand (IVCNZ 2013) (pp. 376-381). Wellington: IEEE Press. doi:10.1109/IVCNZ.2013.6727044
  • Mei, Y., Tang, K., & Yao, X. (2013) "Evolutionary Computation for Dynamic Capacitated Arc Routing Problem". In S. Yang, & X. Yao (Eds.), Evolutionary Computation for Dynamic Optimization Problems. Springer.
  • Mei, Y., Li, X., & Yao, X. (2013) "Decomposing large-scale capacitated arc routing problems using a random route grouping method". In Proceedings of the IEEE Congress on Evolutionary Computation (CEC) (pp. 1013-1020). IEEE. doi:10.1109/CEC.2013.6557678
  • Male, J., Nguyen, S., Zhang, M., & Johnston, M. (2013) "Genetic Programming for Order Acceptance and Scheduling". In Proceedings of 2013 IEEE Congress on Evolutionary Computation (pp. 1005-1012).
  • Male, J., Nguyen, S., Johnston, M., & Zhang, M. (2013) "Evolving Stochastic Dispatching Rules for Order Acceptance and Scheduling via Genetic Programming". In AI 2013: Advances in Artificial Intelligence, Lecture Notes in Computer Science (pp. 478-489).
  • Ma, H., & Schewe, K. D. (2013) "An algebra for geometric conceptual modelling". In 23rd European Japanese Conference on Information Modelling and Knowledge Bases (EJC 2013) (pp. 184-202).
  • Ma, H., Noack, R., Schewe, K. -D., Thalheim, B., & Wang, Q. (2013) "Complete Conceptual Schema Algebras". Fundamenta Informaticae, 123, 271-295. doi:10.3233/FI-2013-834
  • Ma, H., Looser, D., & Schewe, K. (2013) "Using Formal Concept Analysis for Ontology Design and Maintenance in Human Resource Recruitment". In 9th Asia-Pacific Conference on Conceptual Modelling (APCCM) Vol. 143 (pp. 61-68). CRPIT, Australian Computer Society.
  • Lewis, J., & Rhee, T. (2013) "Principal Component Analysis and Laplacian Splines: steps toward a unified model". In Proceedings of the Forum Math for Industry. Fukuoka: FMI.
  • Le, V. L., Welch, I., Gao, X., & Komisarczuk, P. (2013) "Anatomy of drive-by download attack". In Proceedings of the Eleventh Australasian Information Security Conference-Volume 138 (pp. 49-58).
  • Le, V., Welch, I., Gao, X., & Komisarczuk, P. (2013) "Anatomy of Drive-by Download Attack". In Australasian Information Security Conference (ACSW-AISC).
  • Lane, M., Xue, B., Liu, I., & Zhang, M. (2013) "Particle Swarm Optimisation and Statistical Clustering for Feature Selection". In AI2013.
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  • Klapaukh, R., Browne, W., & Zhang, M. (2013) "The Effect of Primitive Sets on the Expression of Evolved Images". In Proceedings of 2013 IEEE Congress on Evolutionary Computation (pp. 725-732).
  • Jabeen, S., Gao, X., & Andreae, P. (2013) "Directional Context Helps: Guiding Semantic Relatedness Computation by Asymmetric Word Associations". In Lecture Notes in Computer Science (pp. 92-101). Springer Berlin Heidelberg. doi:10.1007/978-3-642-41230-1_8
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  • Ghifary, M., Kleijn, W., & Zhang, M. (2013) "Sparse Features in Deep Learning for Noise-Robust Digit Classification". In Proceedings of 2013 the 28th International Conference on Image and Vision Computing New Zealand (IVCNZ2013) (pp. 340-345). IEEE Press.
  • Fu, W., Johnston, M., & Zhang, M. (2013) "Triangular-Distribution-Based Feature Construction Using Genetic Programming for Edge Detection". In Proceedings of 2013 IEEE Congress on Evolutionary Computation (pp. 1732-1739).
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  • Fu, W., Johnston, M., & Zhang, M. (2013) "Genetic Programming for Automatic Construction of Variant Features in Edge Detection". In Applications of Evolutionary Computation (pp. 354-364). Springer Berlin Heidelberg. doi:10.1007/978-3-642-37192-9_36
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  • Ahmed, S., Zhang, M., & Peng, L. (2013) "Feature Selection and Classification of High Dimensional Mass Spectrometry Data: A Genetic Programming Approach". In 11th European Conference, EvoBIO 2013 Vol. 7833 (pp. 43-55). Berlin: Springer.
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