Browsing Computer Science by Title
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Adaptive Locally Constrained Genetic Algorithm For LeastCost Water Distribution Network Design
(IWA Publishing, 2014)This paper describes the development of an adaptive locally constrained genetic algorithm (ALCOGA) 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
(Elsevier, 20150207)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 ... 
Assessment and optimisation of STCA performance: Using the Pareto optimal receiver operating characteristic
(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 tradeoff between ... 
Automated construction of evolutionary algorithm operators for the biobjective water distribution network design problem using a genetic programming based hyperheuristic approach
(IWA Publishing for IAHRIWAIAHS 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 (BWNII)
(American Society of Civil Engineers, 20130518)The Battle of the Water Networks II (BWNII) 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
(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
(IEEE, 2004)Reasoning from data in practical problems is frequently hampered by missing observations. Mixture models provide a powerful general semiparametric method for modelling densities and have close links to radial basis function ... 
A Bayesian Framework for Active Learning
(Institute of Electrical and Electronics Engineers (IEEE), 2010)We describe a Bayesian framework for active learning for nonseparable 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 ... 
Blind source separation for nonstationary mixing
(2000)Blind source separation attempts to recover independent sources which have been linearly mixed to produce observations. We consider blind source separation with nonstationary mixing, but stationary sources. The linear ... 
Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique
(Springer, 2006)Multiple Classifier Systems (MCSs) allow evaluation of the uncertainty of classification outcomes that is of crucial importance for safety critical applications. The uncertainty of classification is determined by a tradeoff ... 
Confidence in Classification: A Bayesian Approach
(Springer Verlag, 2006)Bayesian classification is currently of considerable interest. It provides a strategy for eliminating the uncertainty associated with a particular choice of classifiermodel parameters, and is the optimal decisiontheoretic ... 
Constructing constrainedversion of magic squares using selection hyperheuristics
(Oxford University Press for BCS, The Chartered Institute for IT, 2014)A square matrix of distinct numbers in which every row, column and both diagonals have the same total is referred to as a magic square. Constructing a magic square of a given order is considered a difficult computational ... 
Design of a graphical framework for simple prototyping of pluvial flooding cellular automata algorithms
(Centre for Water Systems, University of Exeter, 2011)Cellular automata (CA) algorithms can be used for quickly describing models of complex systems using simple rules. CADDIES is a new EPSRC and industrysponsored project that aims to use the computational speed of CA ... 
Distance Metric Learning with Eigenvalue Optimization
(Microtome Publishing, 2012)The main theme of this paper is to develop a novel eigenvalue optimization framework for learning a Mahalanobis metric. Within this context, we introduce a novel metric learning approach called DMLeig which is shown to ... 
Dominance Measures for MultiObjective Simulated Annealing
(Institute of Electrical and Electronics Engineers (IEEE), 2004)Simulated annealing (SA) is a provably convergent optimiser for singleobjective (SO) problems. Previously proposed MO extensions have mostly taken the form of an SO SA optimising a composite function of the objectives. ... 
DominanceBased Multiobjective Simulated Annealing
(Institute of Electrical and Electronics Engineers (IEEE), 2008)Simulated annealing is a provably convergent optimizer for singleobjective problems. Previously proposed multiobjective extensions have mostly taken the form of a singleobjective simulated annealer optimizing a composite ... 
Edges of Mutually Nondominating Sets
(ACM, 201307)Multiobjective optimisation yields an estimated Pareto front of mutually nondominating solutions, but with more than three objectives understanding the relationships between solutions is challenging. Natural solutions ... 
Efficiently identifying pareto solutions when objective values change
(ACM, 2014)In many multiobjective problems the objective values assigned to a particular design can change during the course of an optimisation. This may be due to dynamic changes in the problem itself, or updates to estimated ... 
Elite Accumulative Sampling Strategies for Noisy MultiObjective Optimisation
(Springer, 2015)When designing evolutionary algorithms one of the key concerns is the balance between expending function evaluations on exploration versus exploitation. When the optimisation problem experiences observational noise, there ... 
Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions
(Elsevier, 2014)The development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized ...