Parameter tuning of the Firefly Algorithm by standard Monte Carlo and Quasi-Monte Carlo methods

Conference paper


Joy, G., Huyck, C. and Yang, X. 2024. Parameter tuning of the Firefly Algorithm by standard Monte Carlo and Quasi-Monte Carlo methods. Franco, L., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V., Dongarra, J. and Sloot, P. (ed.) 24th International Conference on Computational Science. Malaga, Spain 02 - 04 Jul 2024 Cham Springer. pp. 242–253 https://doi.org/10.1007/978-3-031-63775-9_17
TypeConference paper
TitleParameter tuning of the Firefly Algorithm by standard Monte Carlo and Quasi-Monte Carlo methods
AuthorsJoy, G., Huyck, C. and Yang, X.
Abstract

Almost all optimization algorithms have algorithm-dependent parameters, and the setting of such parameter values can significantly influence the behavior of the algorithm under consideration. Thus, proper parameter tuning should be carried out to ensure that the algorithm used for optimization performs well and is sufficiently robust for solving different types of optimization problems. In this study, the Firefly Algorithm (FA) is used to evaluate the influence of its parameter values on its efficiency. Parameter values are randomly initialized using both the standard Monte Carlo method and the Quasi Monte-Carlo method. The values are then used for tuning the FA. Two benchmark functions and a spring design problem are used to test the robustness of the tuned FA. From the preliminary findings, it can be deduced that both the Monte Carlo method and Quasi-Monte Carlo method produce similar results in terms of optimal fitness values. Numerical experiments using the two different methods on both benchmark functions and the spring design problem showed no major variations in the final fitness values, irrespective of the different sample values selected during the simulations. This insensitivity indicates the robustness of the FA.

KeywordsAlgorithm; Firefly algorithm; Parameter tuning; Monte Carlo; Quasi-Monte Carlo
Sustainable Development Goals9 Industry, innovation and infrastructure
Middlesex University ThemeCreativity, Culture & Enterprise
Research GroupArtificial Intelligence group
Conference24th International Conference on Computational Science
Page range242–253
Proceedings TitleComputational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part V
SeriesLecture Notes in Computer Science
EditorsFranco, L., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V., Dongarra, J. and Sloot, P.
ISSN0302-9743
Electronic1611-3349
ISBN
Paperback9783031637742
Electronic9783031637759
PublisherSpringer
Place of publicationCham
Publication dates
Online28 Jun 2024
Publication process dates
AcceptedMay 2024
Deposited02 Jul 2024
Output statusPublished
Accepted author manuscript
File Access Level
Open
Copyright Statement

This version of the paper has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-ma...), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-031-63775-9_17

Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-031-63775-9_17
Web of Science identifierWOS:001279327300017
Web address (URL) of conference proceedingshttps://doi.org/10.1007/978-3-031-63775-9
LanguageEnglish
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Stochastic decision-making in waste management using a firefly algorithm-driven simulation-optimization approach for generating alternatives
Imanirad, R., Yang, X. and Yeomans, J. 2016. Stochastic decision-making in waste management using a firefly algorithm-driven simulation-optimization approach for generating alternatives. in: Koziel, S., Leifsson, L. and Yang, X. (ed.) Simulation-Driven Modeling and Optimization: ASDOM, Reykjavik, August 2014 Springer.
Economic dispatch using chaotic bat algorithm
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A novel approach for multispectral satellite image classification based on the bat algorithm
Senthilnath, J., Kulkarni, S., Benediktsson, J. and Yang, X. 2016. A novel approach for multispectral satellite image classification based on the bat algorithm. IEEE Geoscience and Remote Sensing Letters. 13 (4), pp. 599-603. https://doi.org/10.1109/LGRS.2016.2530724
Mathematical analysis of energy efficiency optimality in multi-user OFDM systems
Chien, S., Ting, T., Yang, X. and Takahashi, K. 2016. Mathematical analysis of energy efficiency optimality in multi-user OFDM systems. Wireless Communications and Mobile Computing. 16 (3), pp. 252-263. https://doi.org/10.1002/wcm.2516
An improved discrete bat algorithm for symmetric and asymmetric traveling salesman problems
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Advancing ambient assisted living with caution
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Neural constraints and flexibility in language processing
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Navigability analysis of magnetic map with projecting pursuit-based selection method by using firefly algorithm
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Hybrid metaheuristic algorithms: past, present, and future
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Self organising maps with a point neuron model
Huyck, C. and Mitchell, I. 2013. Self organising maps with a point neuron model. Intl Conf. on Cognitive and Neural Systems.
Binary flower pollination algorithm and its application to feature selection
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Computational intelligence and metaheuristic algorithms with applications
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Discrete Cuckoo search applied to job shop scheduling problem
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Swarm intelligence and evolutionary computation: overview and analysis
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Adaptation and hybridization in nature-inspired algorithms
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Solutions of non-smooth economic dispatch problems by swarm intelligence
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A short discussion about economic optimization design of shell-and-tube heat exchangers by a cuckoo-search-algorithm
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Feature selection in life science classification: metaheuristic swarm search
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Diversity and mechanisms in swarm intelligence
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Swarm intelligence based algorithms: a critical analysis
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A comparison of simple agents implemented in simulated neurons
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Programming the MIRTO robot with neurons
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A neuro-computational approach to PP attachment ambiguity resolution
Nadh, K. and Huyck, C. 2012. A neuro-computational approach to PP attachment ambiguity resolution. Neural Computation. 24 (7), pp. 1906-1925. https://doi.org/10.1162/NECO_a_00298
A review of cell assemblies
Huyck, C. and Passmore, P. 2013. A review of cell assemblies. Biological Cybernetics. 107 (3), pp. 263-288. https://doi.org/10.1007/s00422-013-0555-5
Compensatory Hebbian learning for categorisation in simulated biological neural nets
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Planning the sports training sessions with the bat algorithm
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A short discussion about "Economic optimization design of shell-and-tube heat exchangers by a cuckoo-search-algorithm"
Fister, I. (Jr.), Fister, I. and Yang, X. 2015. A short discussion about "Economic optimization design of shell-and-tube heat exchangers by a cuckoo-search-algorithm". Applied Thermal Engineering. 76, pp. 535-537. https://doi.org/10.1016/j.applthermaleng.2014.11.009
Bio-inspired exploring and recruiting tasks in a team of distributed robots over mined regions
De Rango, F., Palmieri, N., Yang, X. and Marano, S. 2015. Bio-inspired exploring and recruiting tasks in a team of distributed robots over mined regions. SPECTS 2015 : International Symposium on Performance Evaluation of Computer and Telecommunication Systems. Chicago, IL, USA 26 - 29 Jul 2015 IEEE. pp. 1-8
Modified bat algorithm with quaternion representation
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A heuristic optimization method inspired by wolf preying behavior
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Sizing optimization of truss structures using flower pollination algorithm
Bekdaş, G., Nigdeli, S. and Yang, X. 2015. Sizing optimization of truss structures using flower pollination algorithm. Applied Soft Computing. 37, pp. 322-331. https://doi.org/10.1016/j.asoc.2015.08.037
Color image segmentation by cuckoo search
Nandy, S., Yang, X., Sarkar, P. and Das, A. 2015. Color image segmentation by cuckoo search. Intelligent Automation & Soft Computing: An International Journal . 21 (4), pp. 673-685.
Random-key cuckoo search for the travelling salesman problem
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A biologically inspired network design model
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Optimum design of frame structures using the eagle strategy with differential evolution
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Analysis of randomisation methods in swarm intelligence
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Analysis of quality-of-service aware orthogonal frequency division multiple access system considering energy efficiency
Ting, T., Yang, X., Lee, S. and Chien, S. 2014. Analysis of quality-of-service aware orthogonal frequency division multiple access system considering energy efficiency. IET Communications. 8 (11), pp. 1947-1954. https://doi.org/10.1049/iet-com.2013.1161
A novel improved accelerated particle swarm optimization algorithm for global numerical optimization
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Oil supply between OPEC and non-OPEC based on game theory
Chang, Y., Yi, J., Yan, W., Yang, X., Zhang, S., Gao, Y. and Wang, X. 2014. Oil supply between OPEC and non-OPEC based on game theory. International Journal of Systems Science. 45 (10), pp. 2127-2132. https://doi.org/10.1080/00207721.2012.762562
Advances of swarm intelligent systems in gene expression data classification
Talatahari, E., Talatahari, S., Gandomi, A. and Yang, X. 2014. Advances of swarm intelligent systems in gene expression data classification. Journal of Multiple-Valued Logic and Soft Computing. 22 (3), pp. 307-315.
Bat algorithm is better than intermittent search strategy
Yang, X., Deb, S. and Fong, S. 2014. Bat algorithm is better than intermittent search strategy. Journal of Multiple-Valued Logic and Soft Computing. 22 (3), pp. 223-237.
Nature-inspired optimization algorithms
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Non-dominated sorting cuckoo search for multiobjective optimization
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Computational optimization, modelling and simulation: past, present and future
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Discrete cuckoo search algorithm for job shop scheduling problem
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Nature-inspired framework for hyperspectral band selection
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A discrete firefly algorithm for the multi-objective hybrid flowshop scheduling problems
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Binary bat algorithm
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Bat algorithm based on simulated annealing and Gaussian perturbations
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Discrete cuckoo search algorithm for the travelling salesman problem
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Cuckoo search: recent advances and applications
Yang, X. and Deb, S. 2014. Cuckoo search: recent advances and applications. Neural Computing and Applications. 24 (1), pp. 169-174. https://doi.org/10.1007/s00521-013-1367-1
Chaotic bat algorithm
Gandomi, A. and Yang, X. 2014. Chaotic bat algorithm. Journal of Computational Science. 5 (2), pp. 224-232. https://doi.org/10.1016/j.jocs.2013.10.002
Mathematical modelling and parameter optimization of pulsating heat pipes
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An empirical study of test effort estimation based on bat algorithm
Srivastava, P., Bidwai, A., Khan, A., Rathore, K., Sharma, R. and Yang, X. 2014. An empirical study of test effort estimation based on bat algorithm. International Journal of Bio-Inspired Computation. 6 (1), pp. 57-70. https://doi.org/10.1504/IJBIC.2014.059966
Bio-inspired computation: success and challenges of IJBIC
Yang, X. and Cui, Z. 2014. Bio-inspired computation: success and challenges of IJBIC. International Journal of Bio-Inspired Computation. 6 (1), pp. 1-6. https://doi.org/10.1504/IJBIC.2014.059969
A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest
Rodrigues, D., Pereira, L., Nakamura, R., Costa, K., Yang, X., Souza, A. and Papa, J. 2014. A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest. Expert Systems with Applications. 41 (5), pp. 2250-2258. https://doi.org/10.1016/j.eswa.2013.09.023
Improved cuckoo search algorithm for hybrid flow shop scheduling problems to minimize makespan
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A bio-inspired algorithm for identification of critical components in the transportation networks
Zhang, X., Adamatzky, A., Yang, H., Mahadaven, S., Yang, X., Wang, Q. and Deng, Y. 2014. A bio-inspired algorithm for identification of critical components in the transportation networks. Applied Mathematics and Computation. 248, pp. 18-27. https://doi.org/10.1016/j.amc.2014.09.055
Post and pre-compensatory Hebbian Learning for categorisation
Huyck, C. and Mitchell, I. 2014. Post and pre-compensatory Hebbian Learning for categorisation. Cognitive Neurodynamics. 8 (4), pp. 299-311. https://doi.org/10.1007/s11571-014-9282-4
A firefly-inspired method for protein structure prediction in lattice models
Maher, B., Albrecht, A., Loomes, M., Yang, X. and Steinhofel, K. 2014. A firefly-inspired method for protein structure prediction in lattice models. Biomolecules. 4 (1), pp. 56-75. https://doi.org/10.3390/biom4010056
True global optimality of the pressure vessel design problem: a benchmark for bio-inspired optimisation algorithms
Yang, X., Huyck, C., Karamanoglu, M. and Khan, N. 2013. True global optimality of the pressure vessel design problem: a benchmark for bio-inspired optimisation algorithms. International Journal of Bio-Inspired Computation. 5 (6), pp. 329-335. https://doi.org/10.1504/IJBIC.2013.058910
Applications and analysis of bio-inspired eagle strategy for engineering optimization
Yang, X., Karamanoglu, M., Ting, T. and Zhao, Y. 2014. Applications and analysis of bio-inspired eagle strategy for engineering optimization. Neural Computing and Applications. 25 (2), pp. 411-420. https://doi.org/10.1007/s00521-013-1508-6
Flower pollination algorithm: a novel approach for multiobjective optimization
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Random walks, Lévy flights, Markov chains and metaheuristic optimization
Yang, X., Ting, T. and Karamanoglu, M. 2013. Random walks, Lévy flights, Markov chains and metaheuristic optimization. in: Future information communication technology and applications: ICFICE 2013 Springer Netherlands.
Are motorways rational from slime mould's point of view?
Adamatzky, A., Akl, S., Alonso-Sanz, R., Van Dessel, W., Ibrahim, Z., Ilachinski, A., Jones, J., Kayem, A., Martínez, G., De Oliveira, P., Prokopenko, M., Schubert, T., Sloot, P., Strano, E. and Yang, X. 2013. Are motorways rational from slime mould's point of view? International Journal of Parallel, Emergent and Distributed Systems. 28 (3), pp. 230-248. https://doi.org/10.1080/17445760.2012.685884
Advances in simulation-driven optimization and modelling
Koziel, S., Leifsson, L. and Yang, X. 2012. Advances in simulation-driven optimization and modelling. Journal of Computational Methods in Science and Engineering. 12 (1-2), pp. 1-4. https://doi.org/10.3233/JCM-2012-0400
Metaheuristic algorithms for self-organizing systems: a tutorial
Yang, X. 2012. Metaheuristic algorithms for self-organizing systems: a tutorial. in: Self-Adaptive and Self-Organizing Systems (SASO), 2012 IEEE Sixth International Conference on IEEE Conference Publications. pp. 249 -250
Integrating nature-inspired optimization algorithms to K-means clustering
Tang, R., Fong, S., Yang, X. and Deb, S. 2012. Integrating nature-inspired optimization algorithms to K-means clustering. in: Seventh International Conference on Digital Information Management (ICDIM), IEEE Conference Publications. pp. 116-123
Wolf search algorithm with ephemeral memory
Rui, T., Fong, S., Yang, X. and Deb, S. 2012. Wolf search algorithm with ephemeral memory. in: Seventh International Conference on Digital Information Management (ICDIM), 2012 IEEE Conference Publications. pp. 165 -172
Metaheuristic applications in structures and infrastructures
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Multi-objective flower algorithm for optimization
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Optimal test sequence generation using firefly algorithm
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Multiobjective firefly algorithm for continuous optimization
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Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems
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Multiobjective cuckoo search for design optimization
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Flower pollination algorithm for global optimization
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Parameter estimation from laser flash experiment data
Wright, L., Yang, X., Matthews, C., Chapman, L. and Roberts, S. 2011. Parameter estimation from laser flash experiment data. in: Computational optimization and applications in engineering and industry studies in computational intelligence Berlin Springer.
Benchmark problems in structural optimization
Gandomi, A. and Yang, X. 2011. Benchmark problems in structural optimization. in: Koziel, S. and Yang, X. (ed.) Computational optimization, methods and algorithms Springer.
Computational optimization: an overview
Yang, X. and Koziel, S. 2011. Computational optimization: an overview. in: Computational Optimization, Methods and Algorithms Springer.
Engineering optimisation by cuckoo search
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Engineering optimization: an introduction with metaheuristic applications
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Metaheuristics in water, geotechnical and transport engineering
Yang, X., Gandomi, A., Talatahari, S. and Alavi, A. 2012. Metaheuristics in water, geotechnical and transport engineering. Elsevier.
Bat algorithm for topology optimization in microelectronic applications
Yang, X., Karamanoglu, M. and Fong, S. 2012. Bat algorithm for topology optimization in microelectronic applications. 1st International Conference on Future Generation Communication Technology. London, UK 12 - 14 Dec 2012 IEEE. pp. 150-155 https://doi.org/10.1109/FGCT.2012.6476566
Rare events forecasting using a residual-feedback GMDH neural network
Fong, S., Nannan, Z., Wong, R. and Yang, X. 2012. Rare events forecasting using a residual-feedback GMDH neural network. in: Seventh International Conference onDigital Information Management (ICDIM), 2012 IEEE Conference Publications. pp. 464-473
Cuckoo search for business optimization applications
Yang, X., Deb, S., Karamanoglu, M. and He, X. 2012. Cuckoo search for business optimization applications. National Conference on Computing and Communication Systems (NCCCS). Durgapur, West Bengal, India 21 - 22 Nov 2012 IEEE. https://doi.org/10.1109/NCCCS.2012.6412973
Bat algorithm for constrained optimization tasks
Gandomi, A., Yang, X., Alavi, A. and Talatahari, S. 2012. Bat algorithm for constrained optimization tasks. Neural Computing and Applications. 22 (6), pp. 1239-1255. https://doi.org/10.1007/s00521-012-1028-9
Efficiency analysis of swarm intelligence and randomization techniques
Yang, X. 2012. Efficiency analysis of swarm intelligence and randomization techniques. Journal of Computational and Theoretical Nanoscience. 9 (2), pp. 189-198. https://doi.org/10.1166/jctn.2012.2012
Modelling of a pulsating heat pipe and start up asymptotics
Yang, X. and Luan, T. 2012. Modelling of a pulsating heat pipe and start up asymptotics. Procedia Computer Science. 9, pp. 784-791. https://doi.org/10.1016/j.procs.2012.04.084
Computational optimization, modelling and simulation: smart algorithms and better models
Yang, X., Koziel, S. and Leifsson, L. 2012. Computational optimization, modelling and simulation: smart algorithms and better models. Procedia Computer Science. 9, pp. 852-856. https://doi.org/10.1016/j.procs.2012.04.091
Free lunch or no free lunch: that is not just a question?
Yang, X. 2012. Free lunch or no free lunch: that is not just a question? International Journal on Artificial Intelligence Tools. 21 (3). https://doi.org/10.1142/S0218213012400106
Coupled eagle strategy and differential evolution for unconstrained and constrained global optimization
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Bat algorithm: a novel approach for global engineering optimization
Yang, X. and Gandomi, A. 2012. Bat algorithm: a novel approach for global engineering optimization. Engineering Computations. 29 (5), pp. 464-483. https://doi.org/10.1108/02644401211235834
Evolutionary boundary constraint handling scheme
Gandomi, A. and Yang, X. 2012. Evolutionary boundary constraint handling scheme. Neural Computing and Applications. 21 (6), pp. 1449-1462. https://doi.org/10.1007/s00521-012-1069-0
Two-stage eagle strategy with differential evolution
Yang, X. and Deb, S. 2012. Two-stage eagle strategy with differential evolution. International Journal of Bio-Inspired Computation. 4 (1), pp. 1-5. https://doi.org/10.1504/IJBIC.2012.044932
Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect
Yang, X., Hosseini, S. and Gandomi, A. 2012. Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect. Applied Soft Computing. 12 (3), pp. 1180-1186. https://doi.org/10.1016/j.asoc.2011.09.017
Cell assemblies for query expansion in information retrieval
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Accelerated particle swarm optimization and support vector machine for business optimization and applications
Yang, X., Deb, S. and Fong, S. 2011. Accelerated particle swarm optimization and support vector machine for business optimization and applications. Fong, S. (ed.) NDT 2011: International Conference on Networked Digital Technologies. Macau, China 11 - 13 Jul 2011 Springer. pp. 53-66 https://doi.org/10.1007/978-3-642-22185-9_6
Bat algorithm for multi-objective optimisation
Yang, X. 2011. Bat algorithm for multi-objective optimisation. International Journal of Bio-Inspired Computation. 3 (5), pp. 267-274. https://doi.org/10.1504/IJBIC.2011.042259
Mixed variable structural optimization using Firefly Algorithm
Gandomi, A., Yang, X. and Alavi, A. 2011. Mixed variable structural optimization using Firefly Algorithm. Computers and Structures. 89 (23-24), pp. 2325-2336. https://doi.org/10.1016/j.compstruc.2011.08.002
Conflict resolution and learning probability matching in a neural cell-assembly architecture
Belavkin, R. and Huyck, C. 2011. Conflict resolution and learning probability matching in a neural cell-assembly architecture. Cognitive Systems Research. 12 (2), pp. 93-101. https://doi.org/10.1016/j.cogsys.2010.08.003
A Pong playing agent modelled with massively overlapping cell assemblies
Nadh, K. and Huyck, C. 2010. A Pong playing agent modelled with massively overlapping cell assemblies. Neurocomputing. 73 (16-18), pp. 2928-2934. https://doi.org/10.1016/j.neucom.2010.07.013
Multi-associative memory in fLIF cell assemblies.
Huyck, C. and Nadh, K. 2009. Multi-associative memory in fLIF cell assemblies. 9th International Conference on Cognitive Modeling. Manchester 24 - 26 Jul 2009
Processing with cell assemblies
Byrne, E. and Huyck, C. 2010. Processing with cell assemblies. Neurocomputing. 74 (1-3), pp. 76-83. https://doi.org/10.1016/j.neucom.2009.09.024
Using cohesive devices to recognize rhetorical relations in text.
Le, H., Abeysinghe, G. and Huyck, C. 2003. Using cohesive devices to recognize rhetorical relations in text. 4th Computational Linguistics UK Research Colloquium (CLUK-4). Edinburgh University Jan 2003 pp. 123-128
Automated discourse segmentation by syntactic information and cue phrases.
Le, H., Abeysinghe, G. and Huyck, C. 2004. Automated discourse segmentation by syntactic information and cue phrases. IASTED International Conference on Artificial Intelligence and Applications (AIA 2004). Innsbruck, Austria 16 - 18 Feb 2004 pp. 293-298
Generating discourse structures for written texts
Le, H., Abeysinghe, G. and Huyck, C. 2004. Generating discourse structures for written texts. International Conference on Computational Linguistics, (COLING 2004). University of Geneva, Switzerland 23 - 27 Aug 2004 pp. 329-355
A study to improve the efficiency of a discourse parsing system
Le, H., Abeysinghe, G. and Huyck, C. 2003. A study to improve the efficiency of a discourse parsing system. 4th International Conference on Intelligent Text Processing and Computational Linguistics, (CICLing’03). Mexico City 16 - 22 Feb 2003 pp. 101-114
Emergence of rules in cell assemblies of fLIF neurons.
Belavkin, R. and Huyck, C. 2008. Emergence of rules in cell assemblies of fLIF neurons. The 18th European Conference on Artificial Intelligence. University of Patras, Greece 21 - 25 Jul 2008
A model of probability matching in a two-choice task based on stochastic control of learning in neural cell-assemblies.
Belavkin, R. and Huyck, C. 2009. A model of probability matching in a two-choice task based on stochastic control of learning in neural cell-assemblies. 9th International conference on cognitive modelling {ICCM 2009]. University of Manchester 24 - 26 Jul 2009
Models of cell assembly decay
Passmore, P. and Huyck, C. 2008. Models of cell assembly decay. Institute of Electrical and Electronics Engineers. pp. 1-6 https://doi.org/10.1109/UKRICIS.2008.4798946
Dialogue based interfaces for universal access.
Huyck, C. 2010. Dialogue based interfaces for universal access. Universal Access in the Information Society. https://doi.org/10.1007/s10209-010-0209-5
A psycholinguistic model of natural language parsing implemented in simulated neurons
Huyck, C. 2009. A psycholinguistic model of natural language parsing implemented in simulated neurons. Cognitive Neurodynamics. 3 (4), pp. 316-330. https://doi.org/10.1007/s11571-009-9080-6
Variable binding by synaptic strength change
Huyck, C. 2009. Variable binding by synaptic strength change. Connection Science. 21 (4), pp. 327-357. https://doi.org/10.1080/09540090902954188
A new metaheuristic bat-inspired algorithm
Yang, X. 2010. A new metaheuristic bat-inspired algorithm. in: González, J., Pelta, D., Cruz, C., Terrazas, G. and Krasnogor, N. (ed.) Nature Inspired Cooperative Strategies for Optimization (NISCO 2010) Berlin Springer.
Eagle strategy using Lévy walk and firefly algorithm for stochastic optimization
Yang, X. and Deb, S. 2010. Eagle strategy using Lévy walk and firefly algorithm for stochastic optimization. in: González, J., Pelta, D, Cruz, C., Terrazas, G. and Krasnogor, N. (ed.) Nature Inspired Cooperative Strategies for Optimization (NICSO 2010) Springer. pp. 101-111
Optimization and data mining for fracture prediction in geosciences
Shi, G. and Yang, X. 2010. Optimization and data mining for fracture prediction in geosciences. Procedia Computer Science. 1 (1), pp. 1359-1366. https://doi.org/10.1016/j.procs.2010.04.151
Firefly algorithm, stochastic test functions and design optimisation
Yang, X. 2010. Firefly algorithm, stochastic test functions and design optimisation. International Journal of Bio-Inspired Computation. 2 (2), pp. 78-84. https://doi.org/10.1504/IJBIC.2010.032124
Oil and gas assessment of the Kuqa depression of Tarim Basin in western China by simple fluid flow models of primary and secondary migrations of hydrocarbons
Shi, G., Zhang, Q., Yang, X. and Mi, S. 2010. Oil and gas assessment of the Kuqa depression of Tarim Basin in western China by simple fluid flow models of primary and secondary migrations of hydrocarbons. Journal of Petroleum Science and Engineering. 75 (1-2), pp. 77-90. https://doi.org/10.1016/j.petrol.2010.10.009
Prepositional phrase attachment ambiguity resolution using semantic hierarchies
Nadh, K. and Huyck, C. 2009. Prepositional phrase attachment ambiguity resolution using semantic hierarchies. Hamza, M. (ed.) 9th IASTED International Conference on Artificial Intelligence and Applications. Innsbruck, Austria 17 - 18 Feb 2009 Acta Press.
Neural cell assemblies for practical applications.
Huyck, C. and Bavan, A. 2002. Neural cell assemblies for practical applications. in: Callaos, N. (ed.) SCI 2002: ISAS: the 6th world multiconference on systemics, cybernetics and informatics: proceedings. Orlando, Florida. International Institute of Informatics and Systemics.. pp. 174-177
Agent design method for enhancing accessibility.
Cook, J., Huyck, C. and Whitney, G. 2004. Agent design method for enhancing accessibility. in: McLoughlin, C. and Cantoni, L. (ed.) ED-MEDIA 2004: world conference on educational multimedia, hypermedia and telecommunications: proceedings of ED-MEDIA 2004. Association for the Advancement of Computing in Education.
Firefly algorithms for multimodal optimization
Yang, X. 2009. Firefly algorithms for multimodal optimization. in: Stochastic Algorithms: Foundations and Applications; 5th International Symposium, SAGA 2009, Sapporo, Japan, October 26-28, 2009. Proceedings Springer.
Cuckoo search via Lévy flights
Yang, X. and Deb, S. 2009. Cuckoo search via Lévy flights. in: World Congress on Nature & Biologically Inspired Computing (NaBIC 2009) IEEE Publications. pp. 210-214
Counting with neurons: rule application with nets of fatiguing leaking integrate and fire neurons.
Huyck, C. and Belavkin, R. 2006. Counting with neurons: rule application with nets of fatiguing leaking integrate and fire neurons. 7th International Conference on Cognitive Modelling. Trieste, Italy pp. 142-147
Creating hierarchical categories using cell assemblies
Huyck, C. 2007. Creating hierarchical categories using cell assemblies. Connection Science. 19 (1), pp. 1-24. https://doi.org/10.1080/09540090600779713
Relevance feedback and cross-language information retrieval
Orengo, V. and Huyck, C. 2006. Relevance feedback and cross-language information retrieval. Information Processing and Management. 42 (5), pp. 1203-1217. https://doi.org/10.1016/j.ipm.2005.12.003
Information retrieval and categorisation using a cell assembly network
Huyck, C. and Orengo, V. 2005. Information retrieval and categorisation using a cell assembly network. Neural Computing and Applications. 14 (4), pp. 282-289. https://doi.org/10.1007/s00521-004-0464-6
Overlapping cell assemblies from correlators
Huyck, C. 2004. Overlapping cell assemblies from correlators. Neural Computing Letters. 56, pp. 435-439. https://doi.org/10.1016/j.neucom.2003.08.003