The Application Of Evolutionary Computation In Parameters Evaluation

Evolutionary computation simulates the evolutionary process of nature, especially the creature species that evolves on stochastic optimization technique. It has characteristics such as self-organization, self-adaptive, self-learning and so on. The population-based searching mechanism makes it suitable run parallel in large scale. Evolutionary computation has found vast application to many science fields, of which evolutionary non-linear parameter evaluation is one direction.The main content of this thesis is discussing how to improve evolutionary algorithm and raising a new evolutionary algorithm and using this new algorithm to parameter evaluation. A large number of computation shows that the new algorithm is a universal, searching-efficiently, converging-quickly algorithm. Data handle problem of the physics experiment of the R. A. Millikan oil drop is solved with evolving algorithm. Getting the greatest common divisor of the minimal data, we will directly obtain electronic quantity and reflect the result of the experiment.In chapter one, the paper have described the overall concept, introduced the origination and the development, the branch of the school and the character of the evolution algorithm, depicted the frame of the algorithm, the method of coding, the design of crossover and mutation, selection strategy, the current situation and trend of research of evolution algorithm.In chapter two, the paper have introduced the problem of parameter estimation, discussed the classical algorithm of the parameter estimation model and some unproved algorithm, In order to keep variety and dynamic adjust-searching area, we put forward to a new evolving algorithm.In chapter three, we settled a model's parameter estimation with this new algorithm, the effect acquired with the new algorithm is better than that acquired with the other algorithms. The result shows that the new algorithm is a one with quality and affectivity.In chapter four, we utilized evolution algorithm to get greatest common divisor of a set of numbers, and solved the concrete problem, the result proves that the new algorithm is affectivity and feasibility.Chapter 5 summarizes the main work of the thesis and describes the work of future.