Data Driven Computing and Machine Learning in Engineering

Advances in Computational Mechanics

ISSN: 1940-5820 (Print);

ISSN: 1940-5839 (Online abstract)

Data Driven Computing and Machine Learning in Engineering
Vol.4, 2019
by Advances in Computational Mechanics
Edited by Xiaoying Zhuang


Preface      

In this age of big data, machine learning techniques have been successfully applied in image processing, genomics, financial problems and even medical diagnosis. The emerging application of machine learning and big data analysis has fundamentally influenced and changed our way of how we think, plan, solve and analyze in engineering. Nevertheless, we are faced with many issues and unsolved problems when applying data drive computing and machine learning in engineering analysis. 


I have conceived the organization of this conference about two years ago with Timon Rabczuk and Hehua Zhu, the presidents of the conference. Now with the financial support of HORIZON-2020-RISE BESTOFRAC project, the International Conference on Data Driven Computing and Machine Learning in Engineering (DACOMA-19) conference is made possible to take place in Shanghai in September 2019.
The conference is co-organized by Tongji University, Leibniz University Hanover, Chinese Society of Computational Mechanics, International Chinese Society of Computational Mechanics, The German Association of Computational Mechanics. This proceeding collects over 100 abstracts from participants of DACOMA-19 presenting research and application in big data technology, data driving computing and artificial intelligence in engineering as well as promoting interdisciplinary topics. 


I hope readers will enjoy reading this proceeding and be inspired from this book in their research in this area. I would like to acknowledge Qimin Wang, Minjing Cai, Bin Li and Wei Peng for their help in collecting and organization of DACOMA.

Xiaoying Zhuang
in Shanghai August 2019 


Data Driven Computing and Machine Learning in Engineering