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Disruptive Technology Forecasting based on Gartner Hype Cycle

机译:基于Gartner炒作周期的破坏性技术预测。

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The continuous breakthrough of scientific research and the emergence of new technologies have made our list of "technologies of tomorrow" longer and longer[1]-[9], and only some of these technologies have the potential to change existing patterns, change people's lifestyles, construct the new value system and bring new products or services to human beings. This part of technology is disruptive technology. Identifying potential disruptive technologies, on the one hand, allows policy makers to predict technology landscape in a timely manner and efficiently allocate resources and funding to the R&D of these technologies. On the other hand, it has universal guiding significance for all kinds of innovators and consumers. In this paper, we propose a discriminate model based on machine learning to identify potential disruptive technologies. Through feature engineering, we extract most characteristic of disruptive technology. We use Gartner Hype Cycle technologies as training data, train our model to identify new disruptive technologies. The model demonstrates how to do technology forecasting in a more controllable, repeatable and verifiable way.
机译:科学研究的持续突破和新技术的出现使我们的“明天技术”列表更长,更长了[1] - [9],只有其中一些技术有可能改变现有模式,改变人的生活方式,构建新的价值系统并为人类带来新产品或服务。这部分技术是破坏性的技术。一方面识别潜在的破坏性技术允许政策制定者及时预测技术景观,并有效地为这些技术的研发提供资金和资金。另一方面,它对各种创新者和消费者具有普遍的指导意义。在本文中,我们提出了一种基于机器学习的判别模型来识别潜在的破坏性技术。通过特征工程,我们提取了破坏性技术的最特色。我们使用Gartner Hype Cycle Technologies作为培训数据,培训我们的模型来识别新的破坏性技术。该模型演示了如何以更可控,可重复和可验证的方式进行技术预测。

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