The performance space measurement of regional innovation system based on neuropsychology |
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| Institution: | 1. The Center for Chinese Modern City Studies, East China Normal University, China;2. School of Urban and Regional Science, East China Normal University, China;1. Department of Electronics and Communication Engineering, Adhi College of Engineering and Technology, Kanchipuram, India;2. School of Information Technology and Engineering, VIT, Vellore, India;3. Department of Computer Science and Engineering, AdhiParasakthi Engineering College, Melmaruvathur, India;4. School of Computer Science and Engineering, RGM College of Engineering and Technology, Nandyal, A.P, India;1. Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India;2. CVR College of Engineering, Hyderabad, Telangana, India;1. Fraunhofer Institute for Systems and Innovation Research (ISI), Breslauer Strasse 48, 76139 Karlsruhe, Germany;2. Copernicus Institute of Sustainable Development, Faculty of Geosciences, Utrecht University, P.O. Box 80115, 3508 TC Utrecht, The Netherlands;1. IT Research Institute at Chosun University, 309, Pilmun-daero, Dong-gu, Gwangju 61452, Republic of Korea;2. Department of Electrical Engineering and Information Technology (DIETI) at the University of Napoli “Federico II”, Via Claudio, 21 80125 Napoli, NA - Italy;3. Hi-Tech Business Headquarter/Hi-Tech MSS Team at SK infosec Co.,Ltd. 46, Pangyo-ro 255beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, Rep. of Korea;4. Division of Undeclared Majors at Chosun University, 309, Pilmun-daero, Dong-gu, Gwangju 61452, Republic of Korea |
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| 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. |
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| Keywords: | Neuropsychology Regional innovation Performance |
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