Classifying movement behaviour in relation to environmental conditions using hidden Markov models.
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Intermittent motion in desert locusts: behavioural complexity in simple environmentsNavigating uncertain waters: a critical review of inferring foraging behaviour from location and dive data in pinnipeds.African elephants adjust speed in response to surface-water constraint on foraging during the dry-seasonIncorrect likelihood methods were used to infer scaling laws of marine predator search behaviourRepeatability of circadian behavioural variation revealed in free-ranging marine fishBayesian State-Space Modelling of Conventional Acoustic Tracking Provides Accurate Descriptors of Home Range Behavior in a Small-Bodied Coastal Fish Species.Animal-borne acoustic transceivers reveal patterns of at-sea associations in an upper-trophic level predatorInvestigating behaviour and population dynamics of striped marlin (Kajikia audax) from the southwest Pacific Ocean with satellite tagsFlexible and practical modeling of animal telemetry data: hidden Markov models and extensions.Objective classification of latent behavioral states in bio-logging data using multivariate-normal hidden Markov models.Joint estimation over multiple individuals improves behavioural state inference from animal movement dataRevisiting the vulnerability of juvenile bigeye (Thunnus obesus) and yellowfin (T. albacares) tuna caught by purse-seine fisheries while associating with surface waters and floating objectsEstimating Density and Temperature Dependence of Juvenile Vital Rates Using a Hidden Markov Model.Behavioural mapping of a pelagic seabird: combining multiple sensors and a hidden Markov model reveals the distribution of at-sea behaviourEffects of temporal resolution on an inferential model of animal movement.Hidden Markov models: the best models for forager movements?Utilisation of intensive foraging zones by female Australian fur seals.Hidden semi-Markov models reveal multiphasic movement of the endangered Florida panther.Structure and dynamics of minke whale surfacing patterns in the Gulf of St. Lawrence, Canada.On the application of mixed hidden Markov models to multiple behavioural time series.Leveraging constraints and biotelemetry data to pinpoint repetitively used spatial features.Evidence for overdispersion in the distribution of malaria parasites and leukocytes in thick blood smears.Incorporating periodic variability in hidden Markov models for animal movement.Taking animal tracking to new depths: synthesizing horizontal--vertical movement relationships for four marine predators.Coupling spectral analysis and hidden Markov models for the segmentation of behavioural patterns.Turn-taking in cooperative offspring care: by-product of individual provisioning behavior or active response rule?Hooded seal Cystophora cristata foraging areas in the Northeast Atlantic Ocean-Investigated using three complementary methods.Assessing acute effects of trapping, handling, and tagging on the behavior of wildlife using GPS telemetry: a case study of the common brushtail possum.Integrating direct observation and GPS tracking to monitor animal behavior for resource management.Integrative modelling of animal movement: incorporating in situ habitat and behavioural information for a migratory marine predator.Estimating behavioral parameters in animal movement models using a state-augmented particle filter.Multi-dimensional Precision Livestock Farming: a potential toolbox for sustainable rangeland management.Understanding the ontogeny of foraging behaviour: insights from combining marine predator bio-logging with satellite-derived oceanography in hidden Markov modelsWhat makes fish vulnerable to capture by hooks? A conceptual framework and a review of key determinantsComparison of methods for determining key marine areas from tracking dataA week in the life of a pygmy blue whale: migratory dive depth overlaps with large vessel draftsSociospatial organization of a solitary carnivore, the Eurasian otter (Lutra lutra)Circumpolar habitat use in the southern elephant seal: implications for foraging success and population trajectoriesFrom high-resolution to low-resolution dive datasets: a new index to quantify the foraging effort of marine predatorsSpace–Time Analysis: Concepts, Quantitative Methods, and Future Directions
P2860
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P2860
Classifying movement behaviour in relation to environmental conditions using hidden Markov models.
description
2009 nî lūn-bûn
@nan
2009年の論文
@ja
2009年学术文章
@wuu
2009年学术文章
@zh-cn
2009年学术文章
@zh-hans
2009年学术文章
@zh-my
2009年学术文章
@zh-sg
2009年學術文章
@yue
2009年學術文章
@zh
2009年學術文章
@zh-hant
name
Classifying movement behaviour ...... ns using hidden Markov models.
@en
Classifying movement behaviour ...... ns using hidden Markov models.
@nl
type
label
Classifying movement behaviour ...... ns using hidden Markov models.
@en
Classifying movement behaviour ...... ns using hidden Markov models.
@nl
prefLabel
Classifying movement behaviour ...... ns using hidden Markov models.
@en
Classifying movement behaviour ...... ns using hidden Markov models.
@nl
P2093
P1476
Classifying movement behaviour ...... ns using hidden Markov models.
@en
P2093
John S Gunn
Marinelle Basson
Mark V Bravington
Toby A Patterson
P304
P356
10.1111/J.1365-2656.2009.01583.X
P577
2009-06-26T00:00:00Z