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Opening date is 10 august 2014 and closing date is 13 august 2014

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Replies to This Discussion


to hum kia karen batane ka purpose yaha post karo ideas. 

method ko describe krna hai to the point not need  solvation..read GDB carefully

which method will be used to solve ...numerically & y?

Romberg's method  improve efficiency so its better..


Aur kia f(x) b find out krna hai??? if yes then value please......................

ni f(x) kch be ni find krna jst tell which mthd is best

Romberg's method   is best offers a very practical tool for numerical integration and derivation.

mth 603 gdb due date 13 aug

Idea solution 

inear multistep method:

Linear multistep methods are used for the numerical solution of ordinary differential equations. Conceptually, a numerical method starts from an initial point and then takes a short step forward in time to find the next solution point. The process continues with subsequent steps to map out the solution. Single-step methods (such as Euler's method) refer to only one previous point and its derivative to determine the current value. Methods such as Runge-Kutta take some intermediate steps (for example, a half-step) to obtain a higher order method, but then discard all previous information before taking a second step. Multistep methods attempt to gain efficiency by keeping and using the information from previous steps rather than discarding it. Consequently, multistep methods refer to several previous points and derivative values. In the case of linear multistep methods, a linear combination of the previous points and derivative values is used.

Numerical methods for ordinary differential equations

Numerical ordinary differential equations is the part of numerical analysis which studies the numerical solution of ordinary differential equations (ODEs). This field is also known under the name numerical integration, but some people reserve this term for the computation of integrals.

Many differential equations cannot be solved analytically; however, in science and engineering, a numeric approximation to the solution is often good enough to solve a problem. The algorithms studied here can be used to compute such an approximation. An alternative method is to use techniques from calculus to obtain a series expansion of the solution.

Ordinary differential equations occur in many scientific disciplines, for instance in physics, chemistry, biology, and economics. In addition, some methods in numerical partial differential equations convert the partial differential equation into an ordinary differential equation, which must then be solved.

kch hasil nh hua discussion parh k :( :(



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