| | Input: Validation and train signals based on the grasshopper optimization algorithm |
| | Output: Included in the RBF kernel parameters are and |
| (1) | while (If the finishing criteria have not been met), do |
| (2) | RBF kernel parameters initialized randomly for and |
| (3) | Initiate the parameters maxiter, pop, Cmax, Cmin, and α |
| (4) | for The GOA algorithm does this for each grasshopper |
| (5) | In SVM, the and are initialized |
| (6) | The SVM evaluates the performance of a model based on selected parameters |
| (7) | Based on equation (11) and and , compute the cost function |
| (8) | If Based on and , cost function should be better than old values, then |
| (9) | New values should be exchanged |
| (10) | Replace grasshopper positions with new and |
| (11) | If Upon satisfaction of the evaluation condition, then |
| (12) | The best position is saved in Td according to the best grasshopper |
| (13) | Updating the and based on the (12) |
| (14) | end if |
| (15) | end if |
| (16) | end for |
| (17) | Find best global γk and Ck |
| (18) | for each grasshopper, do |
| (19) | Updating the position through equation (13) |
| (20) | end for |
| (21) | end while |
