Research Article
[Retracted] Implementing Machine Learning for Supply-Demand Shifts and Price Impacts in Farmer Market for Tool and Equipment Sharing
Algorithm 2
Algorithm for supply-demand optimization.
| (1) | Start | | (2) | Identify the equipment demand (ed), weather forecast (wf), supply (s) | | (3) | | | (4) | While the criteria are not fulfilled | | (5) | For each market i = 1, 2, 3, …, n | | | (a) Determine the total number of farmers who searched and booked the equipment’s y0 | | | (i)Filter the no of farmer who booked a specific equipment y1 | | | (b) Determine the total number of equipment with price x0. | | | (i)Filter the booking of specific equipment with price number x1 | | (6) | Calculate their fitness value f(x1) and f(y1) by using decision tree regressor | | (7) | If f(y1) is greater than f(x1) | | | (a) Replace xi by new price xi+1 according to the MAE value predicted by the model | | (8) | Else | | (9) | If f(x1) is greater than f(y1) | | (b) | Replace xi by new price xi−1 according to the MAE value predicted by the model | | (10) | Else | | (11) | If f(x1) is greater than f(y1) | | | (c) No change | | (12) | End if | | (13) | End if | | (14) | End if | | (15) | End for | | (16) | Update the best solution found so far according to the predicted model | | (17) | End y |
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