Now showing items 1-20 of 201

  • Accurate range-free localization for anisotropic wireless sensor networks 

    Zhang, S; Liu, X; Wang, J; Cao, J; Min, G (Association for Computing Machinery (ACM), 2015-05-01)
    © 2015. Position information plays a pivotal role in wireless sensor network (WSN) applications and protocol/ algorithm design. In recent years, range-free localization algorithms have drawn much research attention due to ...
  • Adaptive Locally Constrained Genetic Algorithm For Least-Cost Water Distribution Network Design 

    Johns, Matthew B.; Keedwell, Edward; Savic, Dragan (IWA Publishing, 2014)
    This paper describes the development of an adaptive locally constrained genetic algorithm (ALCO-GA) and its application to the problem of least cost water distribution network design. Genetic algorithms have been used ...
  • An analysis of the interface between evolutionary algorithm operators and problem features for water resources problems. A case study in water distribution network design 

    McClymont, Kent; Keedwell, Edward; Savic, Dragan (Elsevier, 2015-02-07)
    Evolutionary Algorithms (EAs) have been widely employed to solve water resources problems for nearly two decades with much success. However, recent research in hyperheuristics has raised the possibility of developing ...
  • Ant Colony Optimisation for Exploring Logical Gene-Gene Associations in Genome Wide Association Studies. 

    Sapin, E; Keedwell, E; Frayling, TM (Copicentro Editorial, 2013)
    In this paper a search for the logical variants of gene-gene interactions in genome-wide association study (GWAS) data using ant colony optimisation is proposed. The method based on stochastic algorithms is tested on a ...
  • An Ant Colony Optimization and Tabu List Approach to the Detection of Gene-Gene Interactions in Genome-Wide Association Studies [Research Frontier] 

    Sapin, E; Keedwell, E; Frayling, T (Institute of Electrical and Electronics Engineers (IEEE), 2015-11-01)
    © 2015 IEEE. In this paper, a novel ant colony optimization and tabu list approach for the discovery of gene-gene interactions in genome-wide association study data is proposed. The method is tested on a number of diseases ...
  • Artificial development of connections in SHRUTI networks using a multi-objective genetic algorithm 

    Townsend, J; Keedwell, EC; Galton, A (Association for Computing Machinery (ACM), 2013-07-10)
    SHRUTI is a model of how first-order logic can be represented and reasoned upon using a network of spiking neurons in an attempt to model the brain’s ability to perform reasoning. This paper extends the biological ...
  • An artificial neural network-based rainfall runoff model for improved drainage network modelling 

    Walker, David; Keedwell, EC; Savić, Dragan; Kellagher, R (City University of New York (CUNY): CUNY Academic Works, 2014-08-17)
    Modelling rainfall-runoff processes enables hydrologists to plan their response to flooding events. Urban drainage catchment modelling requires rainfall-runoff models as a prerequisite. In the UK, one of the main software ...
  • Assessment and optimisation of STCA performance: Using the Pareto optimal receiver operating characteristic 

    Reckhouse, William; Everson, Richard M.; Fieldsend, Jonathan E.; Bush, David; Arnold, Trevor; Hayward, Richard; Slater, Keith (2008)
    Short Term Conflict Alert (STCA) systems are complex software programs, with many parameters that must be adjusted to achieve best performance. We describe a simple evolutionary algorithm for optimising the trade-off between ...
  • Automated construction of evolutionary algorithm operators for the bi-objective water distribution network design problem using a genetic programming based hyper-heuristic approach 

    McClymont, Kent; Keedwell, Edward; Savic, Dragan; Randall-Smith, Mark (IWA Publishing for IAHR-IWA-IAHS Joint Committee on Hydroinformatics, 2014)
    The water distribution network (WDN) design problem is primarily concerned with finding the optimal pipe sizes that provide the best service for minimal cost; a problem of continuing importance both in the UK and ...
  • The Battle of the Water Networks II (BWN-II) 

    Marchi, A.; Salomons, E; Ostfeld, A.; Kapelan, Zoran; Simpson, A; Zecchin, A. C.; Maier, H.R.; Wu, Z; Elsayed, S; Song, Y; Walski, T.; Stokes, C; Wu, W; Dandy, G.C.; Alvisi, S; Creaco, Enrico; Franchini, Marco; Saldarriaga, J; Páez, D; Hernandez, David; Bohórquez, J; Bent, R; Coffrin, C; Judi, D; McPherson, T; van Hentenryck, P; Matos, J; Monteiro, A; Matias, N; Yoo, D; Lee, H; Kim, J; Iglesias-Rey, P; Martínez-Solano, F; Mora-Meliá, D; Ribelles-Aguilar, J; Guidolin, Michele; Fu, Guangtao; Reed, P.M.; Wang, Qi; Liu, H; McClymont, K; Johns, Matthew B.; Keedwell, Edward; Kandiah, V; Jasper, M; Drake, K; Shafiee, E; Barandouzi, M; Berglund, A; Brill, D; Mahinthakumar, G; Ranjithan, R; Zechman, E; Morley, Mark S.; Tricarico, Carla; de Marinis, G.; Tolson, B; Khedr, A; Asadzadeh, M (American Society of Civil Engineers, 2013-05-18)
    The Battle of the Water Networks II (BWN-II) is the latest of a series of competitions related to the design and operation of water distribution systems (WDSs) undertaken within the Water Distribution Systems Analysis ...
  • The Bayesian Decision Tree Technique with a Sweeping Strategy 

    Schetinin, Vitaly; Fieldsend, Jonathan E.; Partridge, Derek; Krzanowski, Wojtek J.; Everson, Richard M.; Bailey, Trevor C.; Hernandez, Adolfo (2004)
    The uncertainty of classification outcomes is of crucial importance for many safety critical applications including, for example, medical diagnostics. In such applications the uncertainty of classification can be reliably ...
  • Bayesian estimation and classification with incomplete data using mixture models 

    Zhang, Jufen; Everson, Richard M. (IEEE, 2004)
    Reasoning from data in practical problems is frequently hampered by missing observations. Mixture models provide a powerful general semi-parametric method for modelling densities and have close links to radial basis function ...
  • A Bayesian Framework for Active Learning 

    Fredlund, Richard; Everson, Richard M.; Fieldsend, Jonathan E. (Institute of Electrical and Electronics Engineers (IEEE), 2010)
    We describe a Bayesian framework for active learning for non-separable data, which incorporates a query density to explicitly model how new data is to be sampled. The model makes no assumption of independence between queried ...
  • Bayesian inductively learned modules for safety critical systems 

    Fieldsend, Jonathan E.; Bailey, Trevor C.; Everson, Richard M.; Krzanowski, Wojtek J.; Partridge, Derek; Schetinin, Vitaly (Interface Foundation of North America, Inc., 2003)
    This work examines the use of Bayesian inductively learned software modules for safety critical systems. Central to the safety critical application is the desire to generate confidence measures associated with predictions. ...
  • A Bayesian Methodology for Estimating Uncertainty of Decisions in Safety-Critical Systems 

    Schetinin, Vitaly; Fieldsend, Jonathan E.; Partridge, Derek; Krzanowski, Wojtek J.; Bailey, Trevor C.; Everson, Richard M.; Hernandez, Adolfo (IOS Press, 2006)
  • A Bayesian methodology for estimating uncertainty of decisions in safety-critical systems 

    Schetinin, Vitaly; Fieldsend, Jonathan E.; Partridge, Derek; Krzanowski, Wojtek J.; Everson, Richard M.; Bailey, Trevor C.; Hernandez, Adolfo (IOS Press, 2006)
    Uncertainty of decisions in safety-critical engineering applications can be estimated on the basis of the Bayesian Markov Chain Monte Carlo (MCMC) technique of averaging over decision models. The use of decision tree (DT) ...
  • Bayesian Spectral Analysis with Student-t Noise 

    Christmas, JT (Institute of Electrical and Electronics Engineers (IEEE), 2014-06-01)
    We introduce a Bayesian spectral analysis model for one-dimensional signals where the observation noise is assumed to be Student-t distributed, for robustness to outliers, and we estimate the posterior distributions of the ...
  • Bayesian unsupervised learning with multiple data types 

    Agius, Phaedra; Ying, Yiming; Campbell, Colin (Walter de Gruyter, 2009)
    We propose Bayesian generative models for unsupervised learning with two types of data and an assumed dependency of one type of data on the other. We consider two algorithmic ap- proaches, based on a correspondence model ...
  • Blind source separation for non-stationary mixing 

    Everson, Richard M.; Roberts, Stephen (2000)
    Blind source separation attempts to recover independent sources which have been linearly mixed to produce observations. We consider blind source separation with non-stationary mixing, but stationary sources. The linear ...
  • Cardinality constrained portfolio optimisation 

    Fieldsend, Jonathan E.; Matatko, John; Peng, Ming (Springer Berlin Heidelberg, 2004)
    The traditional quadratic programming approach to portfolio optimisation is difficult to implement when there are cardinality constraints. Recent approaches to resolving this have used heuristic algorithms to search for ...