Solving transcendental equations using Genetic Algorithms
نویسنده
چکیده
Transcendental equations are equations containing trigonometric, algebraic, exponential, logarithmic, etc. terms. Many analytical/iterative methods are used to solve transcendental equations. Though these methods are capable of solving many transcendental equations they suffer from many common disadvantages. Usually transcendental equations have many solutions in a given range, and analytical methods are not able to find all these roots in a given interval, even when they find several solutions, it is not possible to conclude that the given method has found the complete set of roots/solutions, and has not missed any particular solution. Also, these methods fail in case of misbehaved or discontinuous functions. Hence, though these methods may work very well in some situations, they are not general in nature and need a lot of homework from the Analyst.
منابع مشابه
A Robust Method for Solving Transcendental Equations
This paper provides a robust method for solving transcendental equations. The approach, based on the Genetic Algorithm, is commenced with the evaluation of the mathematical equations by their fitness ratio. As the genetic algorithm is a computationally expensive process, the searching space for possible solutions is limited to possible chromosomes for which the function values are closest to ze...
متن کاملNon-Traditional Method-Based Solution for Elimination of Lower Order Harmonics in Voltage Source Inverter Feeding an Induction Motor Drive
This paper presents an efficient and reliable Genetic Algorithm-based solution for Specific Harmonic Elimination (SHE) switching pattern. This method eliminates considerable amount of lower order line voltage harmonics in Pulse Width Modulation (PWM) inverter. The determination of pulse pattern for the elimination of some lower order harmonics of a PWM inverter necessitates solving a system of ...
متن کاملSolving random inverse heat conduction problems using PSO and genetic algorithms
The main purpose of this paper is to solve an inverse random differential equation problem using evolutionary algorithms. Particle Swarm Algorithm and Genetic Algorithm are two algorithms that are used in this paper. In this paper, we solve the inverse problem by solving the inverse random differential equation using Crank-Nicholson's method. Then, using the particle swarm optimization algorith...
متن کاملSolving a Stochastic Cellular Manufacturing Model by Using Genetic Algorithms
This paper presents a mathematical model for designing cellular manufacturing systems (CMSs) solved by genetic algorithms. This model assumes a dynamic production, a stochastic demand, routing flexibility, and machine flexibility. CMS is an application of group technology (GT) for clustering parts and machines by means of their operational and / or apparent form similarity in different aspects ...
متن کاملSOLVING SYSTEMS OF NONLINEAR EQUATIONS IN Rn USING A ROTATING HYPERPLANE IN Rn"
A procedure which accelerates the convergence of iterative methods for the numerical solution of systems of nonlinear algebraic and/or transcendental equations in Rn is introduced. This procedure uses a rotating hyperplane in Rnil, whose rotation axis depends on the current approximation of n 1 components of the solution. The proposed procedure is applied here on the traditional Newton's method...
متن کامل