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Lotka_volterra fitting
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| function train_model(;pguess=[0.8,1.2,1.2,1.0,2.9,1.1]) | |
| println("The initial loss function is $(loss_adjoint(pguess)[1])") | |
| #Train the ODE | |
| resinit=DiffEqFlux.sciml_train(loss_adjoint,pguess,ADAM(), maxiters=3000) | |
| res = DiffEqFlux.sciml_train(loss_adjoint,resinit.minimizer,BFGS(initial_stepnorm = 1e-5)) | |
| println("The parameters are $(res.minimizer) with final loss value $(res.minimum)") | |
| return(res) | |
| end |
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