STP Innovation Management Mechanism Optimization Powered by Advanced Evolutionary IoT Arithmetic

Abstract

Manufacturing has been a key component of a nation's economic growth ever since industrialization.
Accelerated national high technology innovation capacity enhancement and high technology policy innovation
management mechanism optimization driven by advanced evolutionary Internet of Things (IoT) arithmetic are
particularly important given the dual pressures of the new global manufacturing development trend and the
manufacturing industry's loss of competitive advantage. With the use of sophisticated evolutionary IoT
arithmetic, the major body of this research presents an efficient technique for optimizing high technology policy
innovation management mechanisms. A conceptual analysis of currently popular information technologies,
including big data, artificial intelligence, and Internet of Things technologies, as well as an overview of their
application in microgrids, are provided in order to study the optimization of high technology policy innovation
management mechanisms. The STP innovation management mechanism-based approach is used to study all
components in the paper. Ultimately, this technique divides all factors into two categories of cause and effect
factors, and ranks the significance of each factor. Second, with the technical assistance of advanced information
technology like big data and artificial intelligence, a wind power forecast algorithm based on data mining
technology, an enhanced algorithm, and a PV power prediction algorithm based on a deep neural network were
developed. Lastly, it is suggested to use advanced evolutionary IoT arithmetic to drive the innovation
management mechanism for high technology policy majorization.