Wireless Sensor Network Fault Sensor Recognition Algorithm Based on MM* Diagnostic Model
| Autor: | Meili Su, Fulai Pan, Qian Lu, Weixia Gui |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
General Computer Science
Computer science 020208 electrical & electronic engineering Real-time computing General Engineering Hardware_PERFORMANCEANDRELIABILITY 02 engineering and technology Fault (power engineering) Convolutional neural network Diagnostic model Computer Science::Networking and Internet Architecture 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing General Materials Science Recognition algorithm Wireless sensor network Computer Science::Distributed Parallel and Cluster Computing |
| Zdroj: | IEEE Access. 8:127084-127093 |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2020.3008255 |
| Popis: | Wireless Sensor Network (WSN) as one of the representatives of the Internet of Things technology has also received much attention. To accurately diagnose fault sensor nodes, a fault diagnosis method based on fireworks algorithm optimization convolutional neural network algorithm is proposed. The weights and biases of the convolutional neural networks are optimized by using the self-regulating mechanism of global and local searching ability of fireworks algorithm. So the problem of convolution neural network in extreme judgment and limited convergence speed is solved, to effectively realize the fault diagnosis of the WSN. Simulation experiments show that this algorithm has higher fault diagnosis accuracy than other classic WSN fault diagnosis algorithms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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