Approaches to modelling spatio-temporal pattern formation
A review of spatio-temporal pattern analysis approaches on crime analysis
... Spatio-temporal pattern analysis is a key task in crime analysis. Spatio-temporal pattern analysis is a process that extracts information and knowledge from geo-and- ...
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The spatio temporal pattern of urban growth: measurement, analysis and modelling
... growth pattern and their general ...devised approaches and not constrained by the strait jacket of rigid theory devices; therefore, they can be applied on other cities as well, especially in developing ...
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Investigating Spatio Temporal Pattern of Relative Risk of Tuberculosis in Kenya Using Bayesian Hierarchical Approaches
... sian spatio-temporal model for modeling and mapping tuberculosis relative risks in space and time as well identify risks factors associated with the tuber- culosis and counties in Kenya with high ...
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Spatio-temporal modelling for issues in crime and security
... for spatio-temporal analysis and modelling, as outlined above, is well-known, such work has historically received relatively little attention outside the criminological ...its modelling by ...
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Mathematical modelling of spatio-temporal glioma evolution
... ical spatio-temporal evolution of an avascular glioma in an isotropic and homogeneous ...the formation of distinct cell populations with different metabolic profile and invasion ...the ...
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Spatio-temporal sequential pattern mining for tourism sciences
... extracting spatio-temporal meta data from Flickr photos, combining a collection of such photos together results in a spatio-temporal entity movement trail, a trajectory describing an ...
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Hidden Markov models for spatio-temporal pattern recognition
... The problem of finding local rather that global maxima is encountered in many other ar- eas of learning theory and optimisation. These problems are familiar territory to researchers in the artificial neural network ...
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Neural networks as spatio-temporal pattern-forming systems
... ‘neural networks’ where each neuron is represented by a low-dimensional dynamical system. In this review, such models will be considered from the perspective of nonlinear dynamics and general theories of ...
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Evolving spiking neural networks and neurogenetic systems for spatio-and spectro-temporal data modelling and pattern recognition
... computational models of vision, such as the 5-level HMAX model inspired by the information processes in the cortex [92]. However, these models are designed for (static) object recognition (e.g. a picture of a cat), but ...
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A visual analytics framework for spatio-temporal analysis and modelling
... the pattern of the temporal variation in the corresponding subgroup of ...accurate temporal models for the resulting ...regular pattern has been ...
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Modelling and Inference for Spatio-Temporal Marked Point Processes
... point pattern but also some additional features connected to each point, such as the radii of the trees in a forest stand or the amount of seismic energy in ...point pattern in ...considers ...
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Spatio-temporal modelling of wave formation in an excitable chemical medium based on a revised FitzHugh-Nagumo model
... experimental data to generate models which can help to understand the underlying system. This paper aims to seek a revised FHN model, to describe the dynamic behaviours of chemical waves by replacing the Oregonator model ...
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Periodic pattern mining from spatio-temporal trajectory data
... from spatio-temporal trajectories. These previous approaches can target three following issues, (1) long individual trajectory; (2) spatial fuzziness; and (3) temporal ...periodic ...
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Spatio-temporal pattern recognition with evolving spiking neural networks
... Neuro-Genetic Modelling - SNN that incorporate a gene regulatory network (GRN) to capture dynamic interaction of genes related to neuronal activities of the SNN ...
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An integrated, spatio-temporal modelling framework for analysing biological invasions
... is spatio- temporally explicit, the effects of allocating control resources heterogeneously over space and time, for example de- pendent on the distribution pattern of species abundance or hab- itat ...
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MODELLING AND SIMULATION OF A NEUROPHYSIOLOGICAL EXPERIMENT BY SPATIO-TEMPORAL POINT PROCESSES
... stochastic spatio-temporal point process is used to model and quantify ...Two approaches are suggested and the new one based on finite point process density is ...
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Spatio-temporal incremental data modelling for multidimensional environmental analysis
... In response to the aforementioned challenges, it is required for computational environmental analysis to extract, from this data, only the parameters useful for the subsequent decision process (Acciani, Chiarantoni, ...
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Statistical methods for the spatio-temporal modelling of infectious disease spread
... for spatio- temporal epidemic ...purely temporal epidemic ...fitting spatio-temporal epidemic models is etasFLP (Adelfio and Chiodi ...point pattern, ...
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Modelling the spatio-temporal pattern of primary dispersal in stone pine (Pinus pinea L.) stands in the Northern Plateau (Spain)
... dispersal pattern that resulted in a proportion of gaps where no seed arrival is expected (dispersal limitation) between ...the temporal pattern, the proportion of seeds released during monthly ...
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Evolving spiking neural networks for spatio and spectro-temporal pattern recognition
... statistical techniques, e.g. regression techniques; MLP; nearest-neighbour techniques; incremental LDA [41]. State vector transformation, before classification can be done with the use of adaptive incremental ...
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