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Technology Evolution and Technology Forecasting Based on Engineering Big Data

Authors:
Fuhua Wang
Zuhua Jiang
Hong Zheng
Xiaoming Sun
Haili Wang
Xinyu Li

Keywords: data mining; technology evolution; technological paradigm shift; technology forecasting.

Abstract:
Big-data-driven technology innovation management and technology forecasting in engineering design have been a new challenge that we have to cope with. Data mining algorithms, technology evolution methods and technology forecasting models desiderate theoretical breakthroughs and practical innovations. In this paper, the future development trend of technology is forecasted by analyzing engineering big data. The influence of internal and external factors on the evolution path of technology is researched. Hotspots and frontier fields of current technical development are analyzed. Based on technological innovation path and paradigm shift, we explain the mechanism of technology evolution from multiple perspectives, such as individual/group, short-term/long-term, sudden-change/gradual-change. Technology forecasting and results evaluating methods based on the multi-stage evolution mechanism are proposed. The proposal helps enterprises improve their ability to forecast technological development trends of industries, as well as decision ability of technological Research and Development (R&D) innovation.

Pages: 7 to 11

Copyright: Copyright (c) IARIA, 2019

Publication date: July 28, 2019

Published in: conference

ISSN: 2326-9332

ISBN: 978-1-61208-731-3

Location: Nice, France

Dates: from July 28, 2019 to August 2, 2019