The performance space measurement of regional innovation system based on neuropsychology

T. W. Teng, J. Y. Chen

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

In this paper, the performance space measurement of regional innovation system was studied based on neuropsychology. Firstly, the neuropsychology and neural evolution theory were elaborated. Secondly, the genetic algorithm was used to design a regional enterprise performance space measurement model, and this was obtained by connecting the ERP production module and RBF neural network order forecast module. Finally, the algorithm and model constructed in this paper were used to predict the performance of regional foreign trade innovation system. Then, it is concluded that the model constructed in this paper includes the network with the lowest network structure complexity, the smallest training error and the least test error. Therefore, based on this premise, a good neural network that meets the actual needs of users can be obtained, which indicates that the improved method based on evolutionary neural network is effective to measure the performance of regional innovation system.

Original languageEnglish
Pages (from-to)159-166
Number of pages8
JournalCognitive Systems Research
Volume56
DOIs
StatePublished - Aug 2019

Keywords

  • Neuropsychology
  • Performance
  • Regional innovation

Fingerprint

Dive into the research topics of 'The performance space measurement of regional innovation system based on neuropsychology'. Together they form a unique fingerprint.

Cite this