# Parameter discover in odes

**URL:** <https://discourse.julialang.org/t/parameter-discover-in-odes/101243>\
**Category:** New to Julia\
**Created:** [July 6, 2023, 8:03am UTC](https://discourse.julialang.org/t/parameter-discover-in-odes/101243 "2023-07-06T08:03:36Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![Marco\_Nesta](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/marco_nesta/32/50318_2.png) [@Marco\_Nesta](https://discourse.julialang.org/u/Marco_Nesta)\
**Post date:** [July 6, 2023, 8:03am UTC](https://discourse.julialang.org/t/parameter-discover-in-odes/101243/1 "2023-07-06T08:03:36Z")

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I’m new to julia. i’m working on a project where the idea is to use pinns or NODEs to approximate the parameters of the ODEs i’m describing. let me explain better, i have my ODEs and i have the measured data. i want to get to find all the parameters of my ODEs.  
function lotka!(du, u, p, t)  
α, β, γ, δ = p  
du[1] = α \* u[1] - β \* u[2] \* u[1]  
du[2] = γ \* u[1] \* u[2] - δ \* u[2]  
end

For example in this equations I woul like to estimate the parameters having all the x and y value

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<div class="post-metadata">

**Author:** ![Qfl3x](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/qfl3x/32/16227_2.png) [@Qfl3x](https://discourse.julialang.org/u/Qfl3x)\
**Post date:** [July 6, 2023, 8:55am UTC](https://discourse.julialang.org/t/parameter-discover-in-odes/101243/2 "2023-07-06T08:55:30Z")

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For an overview of the SciML parameter estimation: [Parameter Estimation, Bayesian Analysis, and Inverse Problems · Overview of Julia's SciML](https://docs.sciml.ai/Overview/stable/highlevels/inverse_problems/)

For something simple (still part of SciML): [Global Optimization via NLopt · DiffEqParamEstim.jl](https://docs.sciml.ai/DiffEqParamEstim/stable/tutorials/global_optimization/)