Swarm optimisation
Generalised additive multiscale wavelet models constructed using particle swarm optimisation and mutual information for spatio-temporal evolutionary system representation
... Particle swarm optimisation (PSO), originally inspired by some sociological behaviour associated with, for example, bird flocking (Kennedy et ...stochastic optimisation algorithm that was first ...
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Generalised cellular neural networks (GCNNs) constructed using particle swarm optimisation for spatio-temporal evolutionary pattern identification
... particle swarm optimisation (PSO) algorithm, is used to form an initial coarse GCNN model, by recruiting a number of optimised basis functions into the ...
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Transformer incipient fault prediction using combined artificial neural network and various particle swarm optimisation techniques
... In transformer incipient fault recognition, the relationship between gas type and fault is non- linear. This causes problem in the convergence rate and oscillation in artificial neural network (ANN). The parameters of ...
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Optimal power tracker for stand alone photovoltaic system using Artificial Neural Network (ANN) and Particle Swarm Optimisation (PSO)
... Particle Swarm Optimisation (PSO) to optimise the power generation of the PV system based on the solar insolation level, cell temperature, efficiency of PV panel and output voltage ...
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Unit Commitment Solution Using Particle Swarm Optimisation (PSO)
... Since all the previous methods suffer from dimensionality and computation problems, a new method has been evolved in solving the unit commitment. It is known as Particle Swarm Optimisation ...
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A Proficient Segmentation of Mesenchymal Stem Cells by Curvelet OTSU Particle Swarm Optimisation Technique
... tradeoff between the inverse filtering and smoothing. It is clearly known that there is a need to estimate the power spectrum of the original image from the cor- rupted observation in order to implement a Weiner filter. ...
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Self limitation, dynamic and flexible approaches for particle swarm optimisation
... The similar benchmark functions are used for assessment of Dynamic Approaches of Particle Swarm Optimisation as well which consists of thirteen functions with different types of properties. The results ...
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Application of a new multi-agent Hybrid Co-evolution based Particle Swarm Optimisation methodology in ship design
... Particle Swarm Optimisation’ methodology (HCPSO) is ...objective optimisation problems in the area of ship design, where the simultaneous optimisation of several conflicting objectives is ...
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Energy Management of Community Microgrids Considering Uncertainty using Particle Swarm Optimisation
... particle swarm optimisation (MPSO) algorithms to solve optimisa- tion problems of energy management schemes for a community microgrid and proposes a scheduling approach after taking into consideration high ...
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Unit Commitment Solution Using Particle Swarm Optimisation (PSO)
... Abstract— Existing unit commitment methods have the problem of stopping at local optimum and slow convergence. So it is replaced by a new method known as Particle Swarm Optimisation (PSO) which is a ...
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Path Planning in Swarm Robots using Particle Swarm Optimisation on Potential Fields
... Apart from traditional path planning techniques, many algorithms applying Swarm Intelligent techniques in particular Particle Swarm Optimisation over path planning problem were proposed.[r] ...
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Free Search and Particle Swarm Optimisation applied to Non-constrained Test
... Particle Swarm Optimisation (PSO) with variable inertia weight and Free Search (FS) with variable neighbour space applied to non- constrained numerical ...
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Optimisation of PID controller for load frequency control in two area power system using evolutionary particle swarm optimisation
... work, optimisation of parameter values of PID controller for load frequency control in two-area power system using two different particle swarm optimisation algorithms have been successfully ...using ...
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DETERMINISTIC PARTICLE SWARM OPTIMISATION MAXIMUM POWER POINT TRACKER FOR PHOTO VOLTAIC SYSTEM.
... particle swarm optimization technique has been explained to enhance tracking capability for maximum power point of photo voltaic system under uniform irradiation ...
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HYBRID POWER SYSTEM FOR PSO TUNED LOAD FREQUENCY CONTROL
... This paper deals with the Particle Swarm Optimisation (PSO) tuned Load Frequency Control (LFC) of single area power system, with diversified power sources. The diversified generating units considered for ...
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Application of the Bees Algorithm for Constrained Mechanical Design Optimisation Problem
... need optimisation regardless to minimise or ...performance). Optimisation technique is a procedure to find the optimal solution whether it is minimisation or maximisation by comparing other possible ...
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Multistrategy self-organizing map learning for classification problems
... Particle Swarm Optimization (PSO) is commonly implemented in clustering domain due to its capabilities in handling complex data ...Particle Swarm Optimisation which is called ESOMPSO for solving ...
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Estimation of Municipal Solid Waste (MSW) combustion enthalpy for energy recovery
... Particle Swarm Optimisation (PSO) algorithm aimed at predicting the enthalpy of combustion of MSW fuel based on the moisture content (H 2 O), Carbon, Hydrogen, Oxygen, Nitrogen, Sulphur, and Ash ...
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Online Full Text
... Abstract — Related information of optimal cutting parameters for machining and spring force operations is required for process planning. Numerous nonlinear constrained machining models have been developed with the ...
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Algorithms Applied to Global Optimisation – Visual Evaluation
... Regarding dependence on initialisation most dependant and sensitive to initial start locations are Differential Evolution and Particle Swarm Optimisation. These methods could converge very fast to the ...
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