Economic Structure Analysis Based on Neural Network and Bionic Algorithm
In this article, an in-depth study and analysis of economic structure are carried out using a neural network fusion release algorithm. The method system defines the weight space and structure space of neural networks from the perspective of optimization theory, proposes a bionic optimization algorit...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/9925823 |
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| author | Yanjun Dai Lin Su |
| author_facet | Yanjun Dai Lin Su |
| author_sort | Yanjun Dai |
| collection | DOAJ |
| description | In this article, an in-depth study and analysis of economic structure are carried out using a neural network fusion release algorithm. The method system defines the weight space and structure space of neural networks from the perspective of optimization theory, proposes a bionic optimization algorithm under the weight space and structure space, and establishes a neuroevolutionary method with shallow neural network and deep neural network as the research objects. In the shallow neuroevolutionary, the improved genetic algorithm (IGA) based on elite heuristic operation and migration strategy and the improved coyote optimization algorithm (ICOA) based on adaptive influence weights are proposed, and the shallow neuroevolutionary method based on IGA and the shallow neuroevolutionary method based on ICOA are applied to the weight space of backpropagation (BP) neural networks. In deep neuroevolutionary method, the structure space of convolutional neural network is proposed to solve the search space design of neural structure search (NAS), and the GA-based deep neuroevolutionary method under the structure space of convolutional neural network is proposed to solve the problem that numerous hyperparameters and network structure parameters can produce explosive combinations when designing deep learning models. The neural network fusion bionic algorithm used has the application value of exploring the spatial structure and dynamics of the socioeconomic system, improving the perception of the socioeconomic situation, and understanding the development law of society, etc. The idea is also verifiable through the present computer technology. |
| format | Article |
| id | doaj-art-5dd0621dd35441fbb02a423cfadb36af |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-5dd0621dd35441fbb02a423cfadb36af2025-08-20T02:06:03ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/99258239925823Economic Structure Analysis Based on Neural Network and Bionic AlgorithmYanjun Dai0Lin Su1School of Marxism, Dalian University of Technology, Dalian Liaoning 116023, ChinaSchool of Marxism, Dalian University of Technology, Dalian Liaoning 116023, ChinaIn this article, an in-depth study and analysis of economic structure are carried out using a neural network fusion release algorithm. The method system defines the weight space and structure space of neural networks from the perspective of optimization theory, proposes a bionic optimization algorithm under the weight space and structure space, and establishes a neuroevolutionary method with shallow neural network and deep neural network as the research objects. In the shallow neuroevolutionary, the improved genetic algorithm (IGA) based on elite heuristic operation and migration strategy and the improved coyote optimization algorithm (ICOA) based on adaptive influence weights are proposed, and the shallow neuroevolutionary method based on IGA and the shallow neuroevolutionary method based on ICOA are applied to the weight space of backpropagation (BP) neural networks. In deep neuroevolutionary method, the structure space of convolutional neural network is proposed to solve the search space design of neural structure search (NAS), and the GA-based deep neuroevolutionary method under the structure space of convolutional neural network is proposed to solve the problem that numerous hyperparameters and network structure parameters can produce explosive combinations when designing deep learning models. The neural network fusion bionic algorithm used has the application value of exploring the spatial structure and dynamics of the socioeconomic system, improving the perception of the socioeconomic situation, and understanding the development law of society, etc. The idea is also verifiable through the present computer technology.http://dx.doi.org/10.1155/2021/9925823 |
| spellingShingle | Yanjun Dai Lin Su Economic Structure Analysis Based on Neural Network and Bionic Algorithm Complexity |
| title | Economic Structure Analysis Based on Neural Network and Bionic Algorithm |
| title_full | Economic Structure Analysis Based on Neural Network and Bionic Algorithm |
| title_fullStr | Economic Structure Analysis Based on Neural Network and Bionic Algorithm |
| title_full_unstemmed | Economic Structure Analysis Based on Neural Network and Bionic Algorithm |
| title_short | Economic Structure Analysis Based on Neural Network and Bionic Algorithm |
| title_sort | economic structure analysis based on neural network and bionic algorithm |
| url | http://dx.doi.org/10.1155/2021/9925823 |
| work_keys_str_mv | AT yanjundai economicstructureanalysisbasedonneuralnetworkandbionicalgorithm AT linsu economicstructureanalysisbasedonneuralnetworkandbionicalgorithm |