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The Year 3 forecast is calculated by applying the exponential smoothing formula to the Year 2 actual demand and the Year 2 forecast. The actual demand of 365 is weighted by $\alpha=0.4$, and the previous forecast of 310 is weighted by $(1-\alpha)=0.6$, yielding a new forecast of 332.

Conditions: The smoothing constant $\alpha$ is 0.4.; The actual demand for Year 2 ($A_2$) is 365.; The forecast for Year 2 ($F_2$) is 310.

The Year 3 forecast is calculated by applying the exponential smoothing formula to the Year 2 actual demand and the Year 2 forecast. The actual demand of 365 is weighted by $\alpha=0.4$, and the previous forecast of 310 is weighted by $(1-\alpha)=0.6$, yielding a new forecast of 332.

Conditions: The smoothing constant $\alpha$ is 0.4.; The actual demand for Year 2 ($A_2$) is 365.; The forecast for Year 2 ($F_2$) is 310.

To calculate exponential smoothing forecasts step-by-step, first initialize the first forecast equal to the first actual demand. Then, for each subsequent period, substitute the previous period's actual demand and previous forecast into the formula $F_{t+1} = \alpha A_t + (1-\alpha)F_t$ to compute the next forecast, repeating this recursive process until the target period is reached.

Conditions: The smoothing constant $\alpha$ is fixed across all periods.; An initial forecast $F_1$ is established from $A_1$.; Each new forecast depends only on the immediately preceding actual demand and forecast.

To calculate exponential smoothing forecasts step-by-step, first initialize the first forecast equal to the first actual demand. Then, for each subsequent period, substitute the previous period's actual demand and previous forecast into the formula $F_{t+1} = \alpha A_t + (1-\alpha)F_t$ to compute the next forecast, repeating this recursive process until the target period is reached.

Conditions: The smoothing constant $\alpha$ is fixed across all periods.; An initial forecast $F_1$ is established from $A_1$.; Each new forecast depends only on the immediately preceding actual demand and forecast.