Prediction of the number of solitons for initial value of Nonlinear Schrödinger equation based on the CNN
数学专题报告
报告题目(Title)：Prediction of the number of solitons for initial value of Nonlinear Schrödinger equation based on the CNN
报告人(Speaker)：王振（北京航空航天大学教授）
地点(Place)：后主楼1225
时间(Time)：12月28日(周六)，下午17:00-18:00
邀请人(Inviter)：王灯山
报告摘要
The number of solitons emerged in the given initial value for the Nonlinear Schrödinger equation (NLS equation) is explored by the deep learning method. Conventional neural network (CNN) is used to build the framework of prediction. The training data set is constructed by the short time evolution image of initial values of NLS equation by Fourier spectrum method and labelingthem by theoretical results automatically, in other word, Zaharov-Shabat transform for special initial values in form of Asech(x). The prediction ability is verified by different kinds of initial values, including Gaussian initial value and Asech(Ax) initial value. CNN learns the relationship between spatiotemporal data and the number of solitons for given initial values of NLS equation effectively. This method can be used to other integrable equations.
主讲人简介
王振博士，北京航空航天大学数学科学学院教授、博导，研究方向为应用数学方法及其海洋工程应用。承担国家自然科学基金，国家重点研发计划，工信部高技术船舶专项、教育部博士点基金等十余项课题。出版中英文专著各1部，主编教材1部，发表SCI检索论文60余篇。研究成果获教育部自然科学一等奖1项，辽宁省科学技术奖二等奖1项，教育部自然科学二等奖2项，海洋工程科学技术二等奖1项，辽宁省普通高等学校教育教学成果三等奖1项。
