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Multiply those four probabilities together, and you get a combined probability of about one chance in 278 million of all these events coming together in quite this way.
First, we define the four probabilities,,, and for the noiseless case as,,, and.
where cu,vrefers to the above four probabilities, but in the case of random edge detection, i.e. the edges are identified purely by chance.
There are four probabilities for the R L value: (1) for favorable adsorption, 0 < R L < 1, (2) for unfavorable adsorption, R L > 1, (3) for linear adsorption, R L = 1, and (4) for irreversible adsorption, R L = 0.
There are four probabilities for the R L value: for favorable adsorption 0 < R L < 1, for unfavorable adsorption R L > 1, for linear adsorption R L = 1 and for irreversible adsorption R L = 0.
The RL parameter is considered as a more reliable indicator of the adsorption There are four probabilities for the RL value: (1) for favourable adsorption 0 < RL < 1; (2) for unfavourable adsorption RL > 1; (3) for linear adsorption RL = 1, and (4) for irreversible adsorption RL = 0.
Similar(42)
The four probability parameters used in the model were correlated to polymerization temperature, T, and ethylene concentration, [E].
The Dolphins pegged those last three probabilities optimistically as, respectively, 100percent, 1000 percent, and 10percentto100percentcent (dolphins, for example, don't build radio telescopes).
In our case, we considered two probabilities.
Note that there are two probabilities associated with fuzzy modeling.
The three probabilities serve more as comparative than absolute values.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com