6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Construction of Economic Data Management System Based on BP Neural Network

      research-article
      Computational Intelligence and Neuroscience
      Hindawi

      Read this article at

      ScienceOpenPublisherPMC
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          In order to further understand the economic data management system and technology, in-depth research was conducted in the state of people's nervous system feeling. The method of building open platform algorithm to optimize and modify weight rule 2BP grid construction was used to study. According to the basic principle, the BP neural network which is more suitable for economic data management system was constructed. At the same time, to construct economic database resources, neural network system was mainly to simplify and abstract or simulate the human brain nervous system, which is not completely the same, but can also map the basic characteristics of many functions of the human brain. Through the analysis of the economic data of the neural network, the neural network is widely used in the economic data management, which not only improves the management level of enterprises, but also improves the benefits and profits of enterprises. Besides, it has application effect in predicting economic early warning risk analysis cost control strategy management enterprise credit evaluation and enterprise competitiveness evaluation.

          Related collections

          Most cited references29

          • Record: found
          • Abstract: not found
          • Article: not found

          Knowledge-aided Convolutional Neural Network for Small Organ Segmentation

            • Record: found
            • Abstract: not found
            • Article: not found

            Multi-Branch Deep Residual Learning for Clustering and Beamforming in User-Centric Network

              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              VLSI Implementation of a High-Performance Nonlinear Image Scaling Algorithm

              This study implements the VLSI architecture for nonlinear-based picture scaling that is minimal in complexity and memory efficient. Image scaling is used to increase or decrease the size of an image in order to map the resolution of different devices, particularly cameras and printers. Larger memory and greater power are also necessary to produce high-resolution photographs. As a result, the goal of this project is to create a memory-efficient low-power image scaling methodology based on the effective weighted median interpolation methodology. Prefiltering is employed in linear interpolation scaling methods to improve the visual quality of the scaled image in noisy environments. By decreasing the blurring effect, the prefilter performs smoothing and sharpening processes to produce high-quality scaled images. Despite the fact that prefiltering requires more processing resources, the suggested solution scales via effective weighted median interpolation, which reduces noise intrinsically. As a result, a low-cost VLSI architecture can be created. The results of simulations reveal that the effective weighted median interpolation outperforms other existing approaches.

                Author and article information

                Contributors
                Journal
                Comput Intell Neurosci
                Comput Intell Neurosci
                cin
                Computational Intelligence and Neuroscience
                Hindawi
                1687-5265
                1687-5273
                2022
                8 July 2022
                : 2022
                : 9036917
                Affiliations
                School of Economics, Harbin Normal University, Harbin 150025, Heilongjiang, China
                Author notes

                Academic Editor: Rahim Khan

                Author information
                https://orcid.org/0000-0002-4991-7413
                Article
                10.1155/2022/9036917
                9286977
                35845916
                7cf5e086-b17f-4fdc-a289-2583d3da5315
                Copyright © 2022 Xing Han.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 12 April 2022
                : 1 June 2022
                : 23 June 2022
                Categories
                Research Article

                Neurosciences
                Neurosciences

                Comments

                Comment on this article

                Related Documents Log