Each Chapter Of The Book Deals With Mathematical Modelling Through One Or More Specified Techniques. Thus There Are Chapters On Mathematical Modelling Through Algebra, Geometry, Trigonometry And Calculus, Through Ordinary Differential Equations Of First And Second Order, Through Systems Of Differential Equations, Through Difference Equations, Through Partial Differential Equations, Through Functional Equations And Integral Equations, Through Delay-Differential, Differential-Difference And Integro-Differential Equations, Through Calculus Of Variations And Dynamic Programming, Through Graphs, Through Mathematical Programming, Maximum Principle And Maximum Entropy Principle.Each Chapter Contains Mathematical Models From Physical, Biological, Social, Management Sciences And Engineering And Technology And Illustrates Unity In Diversity Of Mathematical Sciences.The Book Contains Plenty Of Exercises In Mathematical Modelling And Is Aimed To Give A Panoramic View Of Applications Of Modelling In All Fields Of Knowledge. It Contains Both Probabilistic And Deterministic Models.The Book Presumes Only The Knowledge Of Undergraduate Mathematics And Can Be Used As A Textbook At Senior Undergraduate Or Post-Graduate Level For A One Or Two- Semester Course For Students Of Mathematics, Statistics, Physical, Social And Biological Sciences And Engineering. It Can Also Be Useful For All Users Of Mathematics And For All Mathematical Modellers.
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Preface 1 i
Mathematical Modelling Through Ordinary Differential
Mathematical Modelling Through Systems of Ordinary
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age-groups algebraic amount boundary Calculus of Variations centre component concave function constant corresponding curve deﬁned denote depends determine difference equation Discuss dx dy dx/dt dynamic Earth edges eigenvalue elements elliptic energy equation models equilibrium position Euler-Lagrange equation EXERCISE expected number ﬁeld Figure ﬁnd ﬁrst ﬁxed points ﬂow ﬂuid force functional equation given gives graph increases inﬁnity integral equation interval investment Laplace linear programming mass Mathematical Modelling matrix maximize maximum entropy maximum value method minimize minimum Model Let models in terms motion negative non-linear obtained orbit ordinary differential equations parabola parallelopiped partial differential equation particle period planet principle of optimality problem proﬁt proportional satisﬁes second order Show signed graph situations solution solve species stability string surface techniques theorem tion trajectories unit variables vector velocity vertex vertices volume zero