… based on a Markov chain model of software usage. The significance of the Markov chain is
twofold. … Analytical results associated with Markov chains facilitate informative analysis of the …

… model based on a first-order Markov chain was developed to simulate daily rainfall at a
point. The model uses historical rainfall data to estimate the Markov … The model is capable of …

… be modelled and predicted as Markov chains. Markov chain models have a relatively simple
… to more complex formulations of stochastic land use models, at least for sketch planning …

… higher-order Markov chain models. In particular, we discuss a class of parsimonious
higher-order Markov chain models. Efficient estimation methods for model parameters based on …

… In this section we report on experiences with E ⊣ MC2 in the context of model checking
two Markov chain models that have been generated from high-level formalisms, namely …

… In this study, we used a Markov chain instead of a high-order stochastic process model to …
built a stationary Markov chain model (simply referred to as a Markov model) of temporal …

… This paper proposes an extension of a single coupled Markov chain model to characterize …
The methodology is based on the concept of conditioning a Markov chain on the future states. …

… The aim of this paper is to assess the applicability of Markov chain models to … model
behaviour will also be useful for large-scale landscape ecosystem models by using Markov chains …

… Markov chain model has been proposed as a mechanism that generates human sleep stages,
A method for estimating the parameters of the model… periodicity, The model simulates both …

… Markov-chain technique is not robust to noise in the data (the mixture level of normal activities
and intrusive activities). The Markov-chain … performance of the Markovchain techniques is …