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Kim et al. [3] developed a system called, AdNext, that uses Bayesian networks to build a transition matrix for the shopping mall clients in order to predict the business type of the next location that a targeted client could visit.
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In their algorithm, they built a transitions matrix that has the probabilities of all the different transitions of an individual to place k after visiting place i and place j.
The transitions between all neighboring Gaussian indices are then used to build a 2-D histogram, which can then be normalized to produce a transition matrix [11].
To build a general modeling framework for MCE systems, the concept of the "energy hub" was proposed with a transition matrix to represent the process of distribution, conversion and storage of different energy carriers [5].
Two matrices mainly influence the model: a Transition matrix TM, and an Emission Matrix EM.
Like the D k matrices above, the entries of these matrices have a transition matrix interpretation.
The transition probabilities of a MC are described by a transition matrix [45].
In addition, the P-DPA algorithm is using an initial distribution matrix and a transition matrix.
The frequencies of transitions between cognitive states were first aggregated in a transition matrix.
A transition matrix (Table 1) illustrates the spectrum and scale of transitions that occurred in the pan-tropics between 1990-2000.
Then, P-DPA will build the initial distribution matrix D that contains the probabilities for every destination to be visited first by individual(x), and it will also build the transition matrix R that contains the probabilities of different transitions of individual(x) from one destination to another. 5.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com