Author Correction: Markov chain-based impact analysis of the pandemic Covid-19 outbreak on global primary energy consumption mix. [PDF]
Sci RepAhmad H +5 more
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Epistemic and aleatoric uncertainty quantification in weather and climate models
Quarterly Journal of the Royal Meteorological Society, EarlyView.Aleatoric and epistemic uncertainties over time on weather and climate time‐scales, estimated through ensembles that sample aleatoric and epistemic uncertainty using Bayesian neural networks for parameterisations in the Lorenz 1996 model. The spread shows the 16th and 84th percentiles.
Laura A. Mansfield +1 more
wiley +1 more source
Spatio-temporal evolution and driving factors of green innovation efficiency in the Chinese urban tourism industry based on spatial Markov chain. [PDF]
Sci RepLiao Z, Liang S, Wang X.
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Nested Markov chain hyper-heuristic (NMHH): a hybrid hyper-heuristic framework for single-objective continuous problems. [PDF]
PeerJ Comput SciBándi N, Gaskó N.
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Predicting Colloidal Interaction Parameters from Small-Angle X-ray Scattering Curves Using Artificial Neural Networks and Markov Chain Monte Carlo Sampling. [PDF]
JACS AuWong K +5 more
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Application of a Multi-Layer Perceptron and Markov Chain Analysis-Based Hybrid Approach for Predicting and Monitoring LULCC Patterns Using Random Forest Classification in Jhelum District, Punjab, Pakistan. [PDF]
Sensors (Basel)Aftab B, Wang Z, Wang S, Feng Z.
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Abstract In Section 7.3, we briefly introduced models for Markov chains in the simple case where there were only two possible responses: an event occurs or not. However, such models have much wider application. In continuous time models, where each subject is in one of several possible states at any given point, they are often called ...
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Abstract Useful models of the real world have to satisfy two conflicting requirements: they must be sufficiently complicated to describe complex systems, but they must also be sufficiently simple for us to analyse them. This chapter introduces Markov chains, which have successfully modelled a huge range of scientific and social phenomena,
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Summary: The Markov chain that has maximum entropy for given first and second moments is determined. The solution provides a discrete analog to the continuous Gauss-Markov process.
Jørn Justesen, Tom Høholdt
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