An Evolutionary approach for solving Shrodinger Equation
The purpose of this paper is to present a method of solving the Shrodinger Equation (SE) by Genetic Algorithms and Grammatical Evolution. The method forms generations of trial solutions expressed in an analytical form. We illustrate the effectiveness of this method providing, for example, the results of its application to a quantum system minimal energy, and we compare these results with those produced by traditional analytical methods.
Keywords: Shrodinger equation, Genetic Algorithms, Grammatical Evolution, Quantum Physics.
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ABOUT THE AUTHORS
Khalid Jebari
Dr computer sciences fuzzy clustering, evolutionary computation, Dynamic optimization
Mohammed Madiafi
Artificial Neural Network, Fuzzy clustering segmentation
Abdelaziz Elmoujahid
computer sciences fuzzy clustering, evolutionary computation, Dynamic optimization
Khalid Jebari
Dr computer sciences fuzzy clustering, evolutionary computation, Dynamic optimization
Mohammed Madiafi
Artificial Neural Network, Fuzzy clustering segmentation
Abdelaziz Elmoujahid
computer sciences fuzzy clustering, evolutionary computation, Dynamic optimization