Improved extreme learning machine based on quantum genetic algorithm and its application
Li Xueyan1,，Liao Yipeng2
(1.College of Artificial Intelligence,Yango University,Fuzhou 350015,China; 2.College of Physics and Information Engineering,Fuzhou University,Fuzhou 350108,China)
Abstract： Artificial neural network is an important learning method of machine learning,and this paper mainly studies the optimization and improvement of the new training method of neural networkthe algorithm of extreme learning machine.This paper firstly studies traditional neural network algorithms,introduces the main ideas and processes of the algorithm, and compares it with the traditional algorithm to show its characteristics and advantages.Secondly,due to the fact that the algorithm has no small flaws in the accuracy of the prediction and the stability of the application,by describing several intelligent optimization algorithms and comparing their advantages and disadvantages, it introduces the focus of this article quantum genetic algorithm,and uses this algorithm to select the optimal weight and threshold to give the test network,to achieve good results.Finally,the steps and processes of the improved limit learning machine algorithm for experimental simulation and result analysis on MATLAB are introduced.The experimental results show that the improved algorithm has an advantage over the classical algorithm in the prediction of regression problems,with higher prediction accuracy and more stable results.The accuracy of classification is also overwhelming.
