|
| Parameter | Meaning |
|
| It is expressed as a specific time known |
| It is a customer’s purchase demand for a specific commodity, at different times is independent of each other, and there is |
| is the variance of the specific probability distribution that the demand data y obeys |
| is the variance of the specific probability distribution subject to the hyperparameter η |
| is the variance of the specific probability distribution subject to the hyperparameter μ |
| is the variance of the specific probability distribution which the hyperparameter ϕ obeys |
| is the variance of the specific probability distribution which the hyperparameter ω obeys |
| is the variance of the specific probability distribution which the hyperparameter λ obeys |
| β is the inverse of the variance of the specific probability distribution which the hyperparameter ω obeys |
| γ is the inverse of the variance of the specific probability distribution which the hyperparameter λ obeys |
| ξ is the inverse of the variance of the specific probability distribution which the hyperparameter μ obeys |
| ζ is the inverse of the variance of the specific probability distribution which the hyperparameter ϕ obeys |
| ε is the noise term or disturbance term acting on at different times |
| H is the period factor of the hyperparameter ω |
| α is the inverse of the variance of the specific probability distribution that the demand data y obeys |
|
| Decision variable | Meaning |
|
| It is a hidden state acting on y, which is represented by the customer's demand state for a specific commodity |
| μ is a hyperparameter acting on η, representing the long-term mean of η, μ ≥ 0 |
| ϕ is a hyperparameter acting on η, indicating the rate of autoregression, −1 < ϕ < 1 |
| η is a hyperparameter acting on y, representing the passenger flow factor, ω ≥ 0 |
| λ is a hyperparameter acting on y, characterized as an additional factor affecting customer demand, λ ≥ 0 |
|
