| Title | A Novel Cloud-IPSO-DBN Algorithm for Evaluating Digital Smart City Construction |
|---|---|
| ID_Doc | 35926 |
| Authors | Yan, HX |
| Title | A Novel Cloud-IPSO-DBN Algorithm for Evaluating Digital Smart City Construction |
| Year | 2023 |
| Published | Ieee Systems Journal, 17, 4 |
| Abstract | A smart city is a kind of urban form that uses technology and data to integrate and optimize urban subsystems and resources to improve urban sustainability and livability. As an important product of the information age, digital smart city combining digital city and smart city has become a significant direction for urban development. In this context, it has become an important task to evaluate construction for digital smart cities. Cloud computing is an Internet-based method, which has excellent performance in Big Data computing and network storage. This article proposes a digital smart city construction evaluation network cloud-IPSO-DBN based on cloud computing and neural network. First, this article improves particle swarm optimization (PSO) algorithm to build improved particle swarm optimization (IPSO). Then, IPSO is used to optimize the initial parameters of deep belief networks (DBN) to build IPSO-DBN for evaluating the construction of digital smart city. Second, this article builds a cloud computing platform to parallelize algorithms to build cloud-IPSO-DBN. This can promote the parallel implementation of the algorithm and improve the performance of the algorithm. Cloud-IPSO-DBN achieves 95.50%/96.00% accuracy, 95.55%/96.11% precision, 95.42%/95.94% recall, and 95.47%/96.02 F1 score on two datasets. |
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