Performance Evaluation of High-Tech Enterprises’ Science and Technological Input Based on BP Neural Network-Reference-Cited by-同舟云学术

Performance Evaluation of High-Tech Enterprises’ Science and Technological Input Based on BP Neural Network

Published:2020 Issue: Volume: Page:1239-1246
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
Short-container-title:

Author:

Wang Qian,Wang Xiaoyu,Zhao Yuxin,Tian Heng

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-5959-4_152

Reference10 articles.

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3. Jinxing, L., Q. Junling, F. Zhihua, et al. 2016. Prediction of soil deformation in tunnelling using artificial neural networks. Computational Intelligence and Neuroscience 2016: 1–16.

4. Yan, F.G., and L.P. Fu. 2016. The research & application on the credit appraisal model of architecture enterprise by the GA-BP neural network. Key Engineering Materials 693: 2022–2030.

5. Umadevi, T., D.K. Naik, R. Sah, et al. 2016. Studies on parameters affecting sinter strength and prediction through artificial neural network model. Mineral Processing and Extractive Metallurgy 125 (1): 32–38.

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