{"title":"On some models based on first order differential equations","authors":"R. Ogunrinde, J. Sunday","doi":"10.5251/AJSIR.2013.4.3.288.293","DOIUrl":null,"url":null,"abstract":"This paper presents some models based on first order differential equations. Such models include population growth, drug distribution in the body and dating archaeological samples models. The paper also discusses the formulations, solutions and applications of such models. Keyword: Models, Growth, Decay, Drug Distribution, and First order INTRODUCTION Over the last few decades, mathematics has broken out into a whole new range of applications in the social sciences, biology, medicine, management, e.t.c. and it seems, almost every field of human endeavor, providing qualitative, if not quantitative models where none had existed or even been contemplated before. Mathematical techniques now play an important role in planning, managerial decision-making, and economics, which has probably been longest quantified of the social sciences (c.f. Burghes etal, 1980). The underlying theme in all applications of mathematics to real situations is the process of mathematical modeling. By this we mean the method of translating a real problem from its initial context into a mathematical description, that is, the mathematical models. This mathematical problem is then solved, and the resulting mathematical solutions must be translated back into the original context. The theory of ordinary differential equations. Equations: On a more practical level, it could be claimed that the spread of modern industrial civilization, for better or for worse, is partly a result of man’s ability to solve the differential equations which govern so many of our industrial processes, be they chemical or engineering (c. f. Burghes et al, 1980) A first order ordinary differential equation is a relation between the derivative of an unknown function x (t), where t is a real variable, the function x itself, the independent variable t, and given function of t. Denoting dt dx by . x (by convention differentiation with respect to t is denoted by a dot, and not by a prime), we assume that in some domain D we can express x as a function of t and x , namely x t f x , . (1) where f is a given function on the subject D (assumed open and connected) of 2 R taking values in R . A function t x which when substituted in (1) reduces it to an identity for each t in some interval (a,b) is called a solution of (1) over the interval (a,b). If f is continuous on D, each solution t x will define a smooth curve in D called an integral curve of the equation. Through each point x t, of D there will pass an integral curve whose gradient at that point is given by x t f , . Which curve we choose as our solution will depend on the initial data given. This is illustrated in Fig. 1 below.","PeriodicalId":7661,"journal":{"name":"American Journal of Scientific and Industrial Research","volume":"11 1","pages":"288-293"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Scientific and Industrial Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5251/AJSIR.2013.4.3.288.293","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents some models based on first order differential equations. Such models include population growth, drug distribution in the body and dating archaeological samples models. The paper also discusses the formulations, solutions and applications of such models. Keyword: Models, Growth, Decay, Drug Distribution, and First order INTRODUCTION Over the last few decades, mathematics has broken out into a whole new range of applications in the social sciences, biology, medicine, management, e.t.c. and it seems, almost every field of human endeavor, providing qualitative, if not quantitative models where none had existed or even been contemplated before. Mathematical techniques now play an important role in planning, managerial decision-making, and economics, which has probably been longest quantified of the social sciences (c.f. Burghes etal, 1980). The underlying theme in all applications of mathematics to real situations is the process of mathematical modeling. By this we mean the method of translating a real problem from its initial context into a mathematical description, that is, the mathematical models. This mathematical problem is then solved, and the resulting mathematical solutions must be translated back into the original context. The theory of ordinary differential equations. Equations: On a more practical level, it could be claimed that the spread of modern industrial civilization, for better or for worse, is partly a result of man’s ability to solve the differential equations which govern so many of our industrial processes, be they chemical or engineering (c. f. Burghes et al, 1980) A first order ordinary differential equation is a relation between the derivative of an unknown function x (t), where t is a real variable, the function x itself, the independent variable t, and given function of t. Denoting dt dx by . x (by convention differentiation with respect to t is denoted by a dot, and not by a prime), we assume that in some domain D we can express x as a function of t and x , namely x t f x , . (1) where f is a given function on the subject D (assumed open and connected) of 2 R taking values in R . A function t x which when substituted in (1) reduces it to an identity for each t in some interval (a,b) is called a solution of (1) over the interval (a,b). If f is continuous on D, each solution t x will define a smooth curve in D called an integral curve of the equation. Through each point x t, of D there will pass an integral curve whose gradient at that point is given by x t f , . Which curve we choose as our solution will depend on the initial data given. This is illustrated in Fig. 1 below.
本文提出了一些基于一阶微分方程的模型。这些模型包括人口增长、体内药物分布和考古样本测年模型。本文还讨论了这些模型的公式、解和应用。在过去的几十年里,数学在社会科学、生物学、医学、管理等领域的应用已经突破了一个全新的范围,似乎几乎在人类努力的每个领域,提供了定性的,如果不是定量的模型,以前没有存在过,甚至没有考虑过。数学技术现在在规划、管理决策和经济学中发挥着重要作用,经济学可能是社会科学中量化时间最长的(c.f. Burghes etal, 1980)。数学在实际情况中的所有应用的基本主题是数学建模的过程。我们指的是将实际问题从其初始环境转化为数学描述的方法,即数学模型。然后解决这个数学问题,并且必须将得到的数学解翻译回原来的上下文中。常微分方程理论。方程:在一个更实际的层面上,它可能会宣称,现代工业文明的传播,不管是好是坏,一部分是由于人的能力来解决微分方程支配我们的许多工业过程,无论是化学或工程(c f。城镇等,1980)一阶常微分方程是一个未知函数的导数之间的关系x (t),其中t是一个真正的变量,函数x本身,独立变量t,并给出t的函数,将dt / dx表示为。x(根据惯例,关于t的微分用一个点来表示,而不是一个素数),我们假设在某个定义域D中,我们可以将* x表示为t和x的函数,即x t f x,。·(1)其中f是2r的给定函数D(假设是开放的和连接的),取R中的值。一个函数t x ,当代入(1)时,将其简化为某个区间(A,b)内每个t的单位,称为(1)在区间(A,b)上的解。如果f在D上连续,每个解t x 将在D上定义一条光滑曲线,称为方程的积分曲线。通过每个点x t (D)会经过一条积分曲线,该点的梯度为x t f (D)。我们选择哪条曲线作为解取决于给出的初始数据。如下图1所示。