Function for Differential Equation for Malthusian Population Approximation

The name of the pictureThe name of the pictureThe name of the pictureClash Royale CLAN TAG#URR8PPP











up vote
-1
down vote

favorite
1












I just rediscovered a program I made a few years ago on Khan Academy to model the Malthusian population curve, based on a differential equation, where $K$ is the population limit, $N$ is the population, and $t$ is time.
$$fracdNdt=frac18logt+frac(K-N)1.69fracsin(t)t$$ It's sort of like a logistic curve, but with some tweaks to better fit real-life.



I was wondering how I should go about finding a function for $y$, the population, with respect to $x$, time. I already know the general logistic growth equation $$fracdNdt=rt(1-fracNK)$$ and how to get to it, but I'm not sure how to tackle my differential equation.



Thanks in advance.




The numerical constants in the first equation are mostly just arbitrary - feel free to replace them with simpler integers if you like.







share|cite|improve this question

















  • 1




    What you call ''equations'' are not equations because there is no $=$ in them. What is $y$ in $frac18log(x)+frac(K-N_o)1.69fracsin(x)x$ ? Sorry I cannot understand your question and what you are looking for.
    – JJacquelin
    Jul 19 at 5:18










  • @JJacquelin Sorry for the confusion. I've edited it now.
    – RayDansh
    Jul 19 at 14:39














up vote
-1
down vote

favorite
1












I just rediscovered a program I made a few years ago on Khan Academy to model the Malthusian population curve, based on a differential equation, where $K$ is the population limit, $N$ is the population, and $t$ is time.
$$fracdNdt=frac18logt+frac(K-N)1.69fracsin(t)t$$ It's sort of like a logistic curve, but with some tweaks to better fit real-life.



I was wondering how I should go about finding a function for $y$, the population, with respect to $x$, time. I already know the general logistic growth equation $$fracdNdt=rt(1-fracNK)$$ and how to get to it, but I'm not sure how to tackle my differential equation.



Thanks in advance.




The numerical constants in the first equation are mostly just arbitrary - feel free to replace them with simpler integers if you like.







share|cite|improve this question

















  • 1




    What you call ''equations'' are not equations because there is no $=$ in them. What is $y$ in $frac18log(x)+frac(K-N_o)1.69fracsin(x)x$ ? Sorry I cannot understand your question and what you are looking for.
    – JJacquelin
    Jul 19 at 5:18










  • @JJacquelin Sorry for the confusion. I've edited it now.
    – RayDansh
    Jul 19 at 14:39












up vote
-1
down vote

favorite
1









up vote
-1
down vote

favorite
1






1





I just rediscovered a program I made a few years ago on Khan Academy to model the Malthusian population curve, based on a differential equation, where $K$ is the population limit, $N$ is the population, and $t$ is time.
$$fracdNdt=frac18logt+frac(K-N)1.69fracsin(t)t$$ It's sort of like a logistic curve, but with some tweaks to better fit real-life.



I was wondering how I should go about finding a function for $y$, the population, with respect to $x$, time. I already know the general logistic growth equation $$fracdNdt=rt(1-fracNK)$$ and how to get to it, but I'm not sure how to tackle my differential equation.



Thanks in advance.




The numerical constants in the first equation are mostly just arbitrary - feel free to replace them with simpler integers if you like.







share|cite|improve this question













I just rediscovered a program I made a few years ago on Khan Academy to model the Malthusian population curve, based on a differential equation, where $K$ is the population limit, $N$ is the population, and $t$ is time.
$$fracdNdt=frac18logt+frac(K-N)1.69fracsin(t)t$$ It's sort of like a logistic curve, but with some tweaks to better fit real-life.



I was wondering how I should go about finding a function for $y$, the population, with respect to $x$, time. I already know the general logistic growth equation $$fracdNdt=rt(1-fracNK)$$ and how to get to it, but I'm not sure how to tackle my differential equation.



Thanks in advance.




The numerical constants in the first equation are mostly just arbitrary - feel free to replace them with simpler integers if you like.









share|cite|improve this question












share|cite|improve this question




share|cite|improve this question








edited Jul 19 at 17:20
























asked Jul 18 at 23:51









RayDansh

882214




882214







  • 1




    What you call ''equations'' are not equations because there is no $=$ in them. What is $y$ in $frac18log(x)+frac(K-N_o)1.69fracsin(x)x$ ? Sorry I cannot understand your question and what you are looking for.
    – JJacquelin
    Jul 19 at 5:18










  • @JJacquelin Sorry for the confusion. I've edited it now.
    – RayDansh
    Jul 19 at 14:39












  • 1




    What you call ''equations'' are not equations because there is no $=$ in them. What is $y$ in $frac18log(x)+frac(K-N_o)1.69fracsin(x)x$ ? Sorry I cannot understand your question and what you are looking for.
    – JJacquelin
    Jul 19 at 5:18










  • @JJacquelin Sorry for the confusion. I've edited it now.
    – RayDansh
    Jul 19 at 14:39







1




1




What you call ''equations'' are not equations because there is no $=$ in them. What is $y$ in $frac18log(x)+frac(K-N_o)1.69fracsin(x)x$ ? Sorry I cannot understand your question and what you are looking for.
– JJacquelin
Jul 19 at 5:18




What you call ''equations'' are not equations because there is no $=$ in them. What is $y$ in $frac18log(x)+frac(K-N_o)1.69fracsin(x)x$ ? Sorry I cannot understand your question and what you are looking for.
– JJacquelin
Jul 19 at 5:18












@JJacquelin Sorry for the confusion. I've edited it now.
– RayDansh
Jul 19 at 14:39




@JJacquelin Sorry for the confusion. I've edited it now.
– RayDansh
Jul 19 at 14:39










1 Answer
1






active

oldest

votes

















up vote
1
down vote



accepted










Let $N_K = N-K$, then we have a slightly simpler equation



$$ fracdN_Kdt + fracasin ttN_K = fracbln t $$



Using the standard first-order method, an integrating factor can be found as



$$ mu(a,t) = expleft(aint_0^t fracsin tautau dtauright) = expbig(a operatornameSi(t) big) $$



where $operatornameSi(t)$ is the sine integral. Then



$$ mu fracdN_Kdt + fracdmudtN_K = fracddtbig(mu N_Kbig) = fracbmuln t $$



$$ implies N_K = frac1muint fracbmuln t dt = be^-aoperatornameSi(t)left[int_0^t frace^aoperatornameSi(tau)ln tau dtau + cright] $$



If $N(0) = N_0$ then we have the solution



$$ N(t) = K + (N_0-K)e^-aoperatornameSi(t) + be^-aoperatornameSi(t)int_0^t frace^aoperatornameSi(tau)ln tau dtau $$



The singularity at $t=1$ can be resolved by the Cauchy principal value. You may notice that this population model grows without bounds, similar to the logarithmic integral.






share|cite|improve this answer























    Your Answer




    StackExchange.ifUsing("editor", function ()
    return StackExchange.using("mathjaxEditing", function ()
    StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix)
    StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
    );
    );
    , "mathjax-editing");

    StackExchange.ready(function()
    var channelOptions =
    tags: "".split(" "),
    id: "69"
    ;
    initTagRenderer("".split(" "), "".split(" "), channelOptions);

    StackExchange.using("externalEditor", function()
    // Have to fire editor after snippets, if snippets enabled
    if (StackExchange.settings.snippets.snippetsEnabled)
    StackExchange.using("snippets", function()
    createEditor();
    );

    else
    createEditor();

    );

    function createEditor()
    StackExchange.prepareEditor(
    heartbeatType: 'answer',
    convertImagesToLinks: true,
    noModals: false,
    showLowRepImageUploadWarning: true,
    reputationToPostImages: 10,
    bindNavPrevention: true,
    postfix: "",
    noCode: true, onDemand: true,
    discardSelector: ".discard-answer"
    ,immediatelyShowMarkdownHelp:true
    );



    );








     

    draft saved


    draft discarded


















    StackExchange.ready(
    function ()
    StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f2856127%2ffunction-for-differential-equation-for-malthusian-population-approximation%23new-answer', 'question_page');

    );

    Post as a guest






























    1 Answer
    1






    active

    oldest

    votes








    1 Answer
    1






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes








    up vote
    1
    down vote



    accepted










    Let $N_K = N-K$, then we have a slightly simpler equation



    $$ fracdN_Kdt + fracasin ttN_K = fracbln t $$



    Using the standard first-order method, an integrating factor can be found as



    $$ mu(a,t) = expleft(aint_0^t fracsin tautau dtauright) = expbig(a operatornameSi(t) big) $$



    where $operatornameSi(t)$ is the sine integral. Then



    $$ mu fracdN_Kdt + fracdmudtN_K = fracddtbig(mu N_Kbig) = fracbmuln t $$



    $$ implies N_K = frac1muint fracbmuln t dt = be^-aoperatornameSi(t)left[int_0^t frace^aoperatornameSi(tau)ln tau dtau + cright] $$



    If $N(0) = N_0$ then we have the solution



    $$ N(t) = K + (N_0-K)e^-aoperatornameSi(t) + be^-aoperatornameSi(t)int_0^t frace^aoperatornameSi(tau)ln tau dtau $$



    The singularity at $t=1$ can be resolved by the Cauchy principal value. You may notice that this population model grows without bounds, similar to the logarithmic integral.






    share|cite|improve this answer



























      up vote
      1
      down vote



      accepted










      Let $N_K = N-K$, then we have a slightly simpler equation



      $$ fracdN_Kdt + fracasin ttN_K = fracbln t $$



      Using the standard first-order method, an integrating factor can be found as



      $$ mu(a,t) = expleft(aint_0^t fracsin tautau dtauright) = expbig(a operatornameSi(t) big) $$



      where $operatornameSi(t)$ is the sine integral. Then



      $$ mu fracdN_Kdt + fracdmudtN_K = fracddtbig(mu N_Kbig) = fracbmuln t $$



      $$ implies N_K = frac1muint fracbmuln t dt = be^-aoperatornameSi(t)left[int_0^t frace^aoperatornameSi(tau)ln tau dtau + cright] $$



      If $N(0) = N_0$ then we have the solution



      $$ N(t) = K + (N_0-K)e^-aoperatornameSi(t) + be^-aoperatornameSi(t)int_0^t frace^aoperatornameSi(tau)ln tau dtau $$



      The singularity at $t=1$ can be resolved by the Cauchy principal value. You may notice that this population model grows without bounds, similar to the logarithmic integral.






      share|cite|improve this answer

























        up vote
        1
        down vote



        accepted







        up vote
        1
        down vote



        accepted






        Let $N_K = N-K$, then we have a slightly simpler equation



        $$ fracdN_Kdt + fracasin ttN_K = fracbln t $$



        Using the standard first-order method, an integrating factor can be found as



        $$ mu(a,t) = expleft(aint_0^t fracsin tautau dtauright) = expbig(a operatornameSi(t) big) $$



        where $operatornameSi(t)$ is the sine integral. Then



        $$ mu fracdN_Kdt + fracdmudtN_K = fracddtbig(mu N_Kbig) = fracbmuln t $$



        $$ implies N_K = frac1muint fracbmuln t dt = be^-aoperatornameSi(t)left[int_0^t frace^aoperatornameSi(tau)ln tau dtau + cright] $$



        If $N(0) = N_0$ then we have the solution



        $$ N(t) = K + (N_0-K)e^-aoperatornameSi(t) + be^-aoperatornameSi(t)int_0^t frace^aoperatornameSi(tau)ln tau dtau $$



        The singularity at $t=1$ can be resolved by the Cauchy principal value. You may notice that this population model grows without bounds, similar to the logarithmic integral.






        share|cite|improve this answer















        Let $N_K = N-K$, then we have a slightly simpler equation



        $$ fracdN_Kdt + fracasin ttN_K = fracbln t $$



        Using the standard first-order method, an integrating factor can be found as



        $$ mu(a,t) = expleft(aint_0^t fracsin tautau dtauright) = expbig(a operatornameSi(t) big) $$



        where $operatornameSi(t)$ is the sine integral. Then



        $$ mu fracdN_Kdt + fracdmudtN_K = fracddtbig(mu N_Kbig) = fracbmuln t $$



        $$ implies N_K = frac1muint fracbmuln t dt = be^-aoperatornameSi(t)left[int_0^t frace^aoperatornameSi(tau)ln tau dtau + cright] $$



        If $N(0) = N_0$ then we have the solution



        $$ N(t) = K + (N_0-K)e^-aoperatornameSi(t) + be^-aoperatornameSi(t)int_0^t frace^aoperatornameSi(tau)ln tau dtau $$



        The singularity at $t=1$ can be resolved by the Cauchy principal value. You may notice that this population model grows without bounds, similar to the logarithmic integral.







        share|cite|improve this answer















        share|cite|improve this answer



        share|cite|improve this answer








        edited Jul 20 at 14:28


























        answered Jul 19 at 17:00









        Dylan

        11.4k31026




        11.4k31026






















             

            draft saved


            draft discarded


























             


            draft saved


            draft discarded














            StackExchange.ready(
            function ()
            StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f2856127%2ffunction-for-differential-equation-for-malthusian-population-approximation%23new-answer', 'question_page');

            );

            Post as a guest













































































            Comments

            Popular posts from this blog

            What is the equation of a 3D cone with generalised tilt?

            Color the edges and diagonals of a regular polygon

            Relationship between determinant of matrix and determinant of adjoint?