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Exploring resource management for innovation power network based on deep learning algorithm

  • S.I. : SPIoT 2020
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

Innovation network is an autocatalytic network; however, there are several factors that affect the process and result. In the beginning, the innovation is very difficult due to certain blocked factors. Based on the machine learning network resource fusion algorithm, this paper conducts research on the innovation process and innovation driving force based on autocatalytic network. An autocatalytic network is introduced to explain the innovation process, including the evolutionary mechanism, evolution law, and the critical property of system innovation. It is concluded that the key of innovation is to unlock some key effect factors in core or find the key factors that connect different innovation. At last, the evolution law and the critical point are given, which could make us make sound and timely decisions.

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Authors and Affiliations

  1. School of Finance, Harbin University of Commerce, Harbin, 150028, China

    Congmin Liu

  2. School of Business Administration, Lab of Management, Decision, and Information System, Weifang University of Science and Technology, 166 Xueyuan Road, Shouguang, 262700, Shandong, China

    Xiaojing Zheng

Authors
  1. Congmin Liu
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  2. Xiaojing Zheng
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Correspondence to Xiaojing Zheng.

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Liu, C., Zheng, X. Exploring resource management for innovation power network based on deep learning algorithm. Neural Comput & Applic 33, 4013–4025 (2021). https://doi.org/10.1007/s00521-020-05446-w

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  • DOI: https://doi.org/10.1007/s00521-020-05446-w

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